test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    def test_pt_bart_classifier(test_device):
        compiler_cfg = _get_global_compiler_config()
        compiler_cfg.compile_depth = CompileDepth.SPLIT_GRAPH
    
        model_name = f"facebook/bart-large-mnli"
        model = download_model(BartForSequenceClassification.from_pretrained, model_name, torchscript=True)
        tokenizer = download_model(BartTokenizer.from_pretrained, model_name, pad_to_max_length=True)
        hypothesis = "Most of Mrinal Sen's work can be found in European collections."
        premise = "Calcutta seems to be the only other production center having any pretensions to artistic creativity at all, but ironically you're actually more likely to see the works of Satyajit Ray or Mrinal Sen shown in Europe or North America than in India itself."
    
        # generate inputs
        inputs_dict = tokenizer(
            premise,
            hypothesis,
            truncation=True,
            padding="max_length",
            max_length=256,
            truncation_strategy="only_first",
            return_tensors="pt",
        )
        decoder_input_ids = shift_tokens_right(
            inputs_dict["input_ids"], model.config.pad_token_id, model.config.decoder_start_token_id
        )
        inputs = [inputs_dict["input_ids"], inputs_dict["attention_mask"], decoder_input_ids]
    
        # Compile & feed data
        pt_mod = BartWrapper(model.model)
    
>       compiled_model = forge.compile(pt_mod, sample_inputs=inputs, module_name="pt_bart")

forge/test/models/pytorch/text/bart/test_bart.py:55: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

context = CompileContext(modules=[Module pt_bart], graph_name='pt_bart', compiler_cfg=CompilerConfig(enable_training=False, enab...in_recompile=False, recompile_count=0, target_cycles_offset=0, forge_module=None, compiled_binary=None, attach_to=None)

    def run_optimization_pass(context: CompileContext) -> CompileDepth:
        """
        Runs optimization passes.
    
        Parameters
        ----------
        context: CompileContext
            Compile context
    
        Returns
        -------
        CompileDepth - next compile stage
        """
        compiler_cfg = context.compiler_cfg
        graph_name = context.graph_name
        graph, intermediate_tensors = context.graph, context.intermediate_tensors
    
>       run_optimization_graph_passes(graph)
E       RuntimeError: TT_ASSERT @ /__w/tt-forge-fe/tt-forge-fe/forge/csrc/passes/commute_utils.cpp:1105: reshape->op_name() == "reshape"
E       info:
E       update_reshape_attr called for a non-reshape operation
E       backtrace:
E        --- tt::passes::update_reshape_attr(tt::graphlib::OpNode*, tt::graphlib::Shape)
E        --- tt::passes::commute_and_bypass(tt::graphlib::Graph*, std::vector<tt::graphlib::Node*, std::allocator<tt::graphlib::Node*> > const&)
E        --- tt::passes::erase_inverse_ops(tt::graphlib::Graph*)
E        --- tt::run_optimization_graph_passes(tt::graphlib::Graph*)
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xfc649) [0x7f1800a55649]
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xdf905) [0x7f1800a38905]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x18b282) [0x5618e4ac0282]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x5c7d) [0x5618e4aaff4d]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0x122) [0x5618e4ace882]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x818) [0x5618e4aaaae8]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0xbb) [0x5618e4ace81b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]

forge/forge/compile.py:785: RuntimeError

test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    def test_bert_sequence_classification_pytorch(test_device):
        model, inputs, _ = generate_model_bert_seqcls_hf_pytorch(
            "textattack/bert-base-uncased-SST-2",
        )
    
        compiled_model = forge.compile(model, sample_inputs=inputs, module_name="pt_bert_sequence_classification")
    
>       co_out = compiled_model(*inputs)
E       TypeError: 'CompileResults' object is not callable

forge/test/models/pytorch/text/bert/test_bert.py:141: TypeError

variant = 'EleutherAI/gpt-neo-125M', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_gptneo_causal_lm(variant, test_device):
        # Set random seed for repeatability
        torch.manual_seed(42)
    
        # Configurations
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        # Load tokenizer and model
        # Variants: # EleutherAI/gpt-neo-125M, EleutherAI/gpt-neo-1.3B,
        # EleutherAI/gpt-neo-2.7B
    
        config = download_model(GPTNeoConfig.from_pretrained, variant)
        config_dict = config.to_dict()
        config_dict["return_dict"] = False
        config_dict["use_cache"] = False
        config = GPTNeoConfig(**config_dict)
    
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
        model = download_model(GPTNeoForCausalLM.from_pretrained, variant, config=config)
    
        # Sample input text
        prompt = "My name is Bert, and I am"
    
        inputs = tokenizer(prompt, return_tensors="pt", max_length=256, pad_to_max_length=True, truncation=True)
    
        # Wrapper to get around attention mask
        class Wrapper(torch.nn.Module):
            def __init__(self, model):
                super().__init__()
                self.model = model
    
            def forward(self, input_ids, attention_mask):
                return self.model(input_ids, None, attention_mask)
    
        inputs = [inputs["input_ids"], inputs["attention_mask"]]
>       compiled_model = forge.compile(
            Wrapper(model),
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_causal_lm",
        )

forge/test/models/pytorch/text/gptneo/test_gptneo.py:65: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
forge/forge/compile.py:634: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
forge/forge/compile.py:973: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
forge/forge/tvm_to_python.py:2136: in generate_forge_module
    verify_framework_vs_forge_codegen(framework_outputs, forge_outputs, verify_cfg=verify_cfg)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

frame_outputs = [tensor([[[ -2.93149,  -3.04098,  -5.19186,  ..., -11.81308,  -8.60934,  -6.07345],
         [ -6.99371,  -5.94796, -1...],
         [-38.90412, -38.28091, -42.97676,  ..., -69.93178, -49.82716, -37.80742]]], grad_fn=<UnsafeViewBackward0>)]
forge_outputs = (Forge Tensor: tensor([[[ -2.93151,  -3.04100,  -5.19192,  ..., -11.81311,  -8.60940,  -6.07350],
         [ -6.99369,...2,  -5.60490,  -4.23273,  ..., -16.88002, -15.43275,  -9.50537]]], grad_fn=<UnsafeViewBackward0>), DataFormat.Float32,)
verify_cfg = DepricatedVerifyConfig(graph_name='graph', enabled=False, intermediates=False, rtol={torch.float32: None, torch.float1...ent_checking=True, enable_parameter_gradient_checking=True, _input_gradient_queue=None, _parameter_gradient_queue=None)

    def verify_framework_vs_forge_codegen(frame_outputs, forge_outputs, verify_cfg):
        from forge.verify.compare import compare_tensor_to_golden
    
        test_pass = True
        for i, (golden, output) in enumerate(zip(frame_outputs, forge_outputs)):
            test_pass &= compare_tensor_to_golden(
                f"Framework vs. Forge codegen output {i}", golden, output.value(), is_forge=False, verify_cfg=verify_cfg
            )
    
>           assert test_pass, f"Data mismatch on output {i} between framework and Forge codegen"
E           AssertionError: Data mismatch on output 0 between framework and Forge codegen

forge/forge/tvm_to_python.py:1985: AssertionError

variant = 'EleutherAI/gpt-neo-1.3B', test_device = None

    @pytest.mark.nightly
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_gptneo_sequence_classification(variant, test_device):
        # Load tokenizer and model from HuggingFace
        # Variants: # EleutherAI/gpt-neo-125M, EleutherAI/gpt-neo-1.3B,
        # EleutherAI/gpt-neo-2.7B
    
        # Configurations
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
        model = download_model(GPTNeoForSequenceClassification.from_pretrained, variant, torchscript=True)
    
        # Load data sample
        review = "the movie was great!"
    
        # Data preprocessing
        input_tokens = tokenizer(
            review,
            max_length=32,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        class Wrapper(torch.nn.Module):
            def __init__(self, model):
                super().__init__()
                self.model = model
    
            def forward(self, input_ids, attention_mask):
                return self.model(input_ids, None, attention_mask)
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
    
>       compiled_model = forge.compile(
            Wrapper(model),
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_seq_cls",
        )

forge/test/models/pytorch/text/gptneo/test_gptneo.py:116: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
forge/forge/compile.py:634: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
forge/forge/compile.py:973: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
forge/forge/tvm_to_python.py:2136: in generate_forge_module
    verify_framework_vs_forge_codegen(framework_outputs, forge_outputs, verify_cfg=verify_cfg)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

frame_outputs = [tensor([[ 2.02300, -1.06290]], grad_fn=<IndexBackward0>), tensor([[[[-8.65128e-02,  1.82043e-01,  2.00490e-01,  ..., ...51],
          [ 0.65266,  0.77656, -0.42172,  ..., -0.43564,  0.00645, -0.18691]]]], grad_fn=<PermuteBackward0>), ...]
forge_outputs = (Forge Tensor: tensor([[ 2.36522, -0.28600]], grad_fn=<IndexBackward0>), DataFormat.Float32, Forge Tensor: tensor([[[[...40,  0.44998, -0.12259,  ..., -0.48345,  0.07875, -0.03002]]]], grad_fn=<TransposeBackward0>), DataFormat.Float32, ...)
verify_cfg = DepricatedVerifyConfig(graph_name='graph', enabled=False, intermediates=False, rtol={torch.float32: None, torch.float1...ent_checking=True, enable_parameter_gradient_checking=True, _input_gradient_queue=None, _parameter_gradient_queue=None)

    def verify_framework_vs_forge_codegen(frame_outputs, forge_outputs, verify_cfg):
        from forge.verify.compare import compare_tensor_to_golden
    
        test_pass = True
        for i, (golden, output) in enumerate(zip(frame_outputs, forge_outputs)):
            test_pass &= compare_tensor_to_golden(
                f"Framework vs. Forge codegen output {i}", golden, output.value(), is_forge=False, verify_cfg=verify_cfg
            )
    
>           assert test_pass, f"Data mismatch on output {i} between framework and Forge codegen"
E           AssertionError: Data mismatch on output 3 between framework and Forge codegen

forge/forge/tvm_to_python.py:1985: AssertionError

variant = 'EleutherAI/gpt-neo-2.7B', test_device = None

    @pytest.mark.nightly
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_gptneo_sequence_classification(variant, test_device):
        # Load tokenizer and model from HuggingFace
        # Variants: # EleutherAI/gpt-neo-125M, EleutherAI/gpt-neo-1.3B,
        # EleutherAI/gpt-neo-2.7B
    
        # Configurations
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
        model = download_model(GPTNeoForSequenceClassification.from_pretrained, variant, torchscript=True)
    
        # Load data sample
        review = "the movie was great!"
    
        # Data preprocessing
        input_tokens = tokenizer(
            review,
            max_length=32,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        class Wrapper(torch.nn.Module):
            def __init__(self, model):
                super().__init__()
                self.model = model
    
            def forward(self, input_ids, attention_mask):
                return self.model(input_ids, None, attention_mask)
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
    
>       compiled_model = forge.compile(
            Wrapper(model),
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_seq_cls",
        )

forge/test/models/pytorch/text/gptneo/test_gptneo.py:116: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
forge/forge/compile.py:634: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
forge/forge/compile.py:973: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
forge/forge/tvm_to_python.py:2136: in generate_forge_module
    verify_framework_vs_forge_codegen(framework_outputs, forge_outputs, verify_cfg=verify_cfg)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

frame_outputs = [tensor([[-1.73945,  3.86908]], grad_fn=<IndexBackward0>), tensor([[[[-0.84780, -0.45597, -0.50286,  ...,  0.32681, -0...70],
          [-0.14309, -0.12644, -0.26851,  ...,  0.24723,  0.67294,  0.32695]]]], grad_fn=<PermuteBackward0>), ...]
forge_outputs = (Forge Tensor: tensor([[ 1.12671, -1.29598]], grad_fn=<IndexBackward0>), DataFormat.Float32, Forge Tensor: tensor([[[[....37702e-03,  ..., -3.20576e-01,  7.41636e-01, -2.53812e-01]]]], grad_fn=<TransposeBackward0>), DataFormat.Float32, ...)
verify_cfg = DepricatedVerifyConfig(graph_name='graph', enabled=False, intermediates=False, rtol={torch.float32: None, torch.float1...ent_checking=True, enable_parameter_gradient_checking=True, _input_gradient_queue=None, _parameter_gradient_queue=None)

    def verify_framework_vs_forge_codegen(frame_outputs, forge_outputs, verify_cfg):
        from forge.verify.compare import compare_tensor_to_golden
    
        test_pass = True
        for i, (golden, output) in enumerate(zip(frame_outputs, forge_outputs)):
            test_pass &= compare_tensor_to_golden(
                f"Framework vs. Forge codegen output {i}", golden, output.value(), is_forge=False, verify_cfg=verify_cfg
            )
    
>           assert test_pass, f"Data mismatch on output {i} between framework and Forge codegen"
E           AssertionError: Data mismatch on output 0 between framework and Forge codegen

forge/forge/tvm_to_python.py:1985: AssertionError

variant = 'facebook/opt-350m', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_opt_causal_lm(variant, test_device):
        # Load tokenizer and model from HuggingFace
        # Variants: "facebook/opt-125m", "facebook/opt-350m", "facebook/opt-1.3b"
    
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        config = OPTConfig.from_pretrained(variant)
        config_dict = config.to_dict()
        config_dict["return_dict"] = False
        config_dict["use_cache"] = False
        config = OPTConfig(**config_dict)
        model = download_model(OPTForCausalLM.from_pretrained, variant, config=config)
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
    
        # Input sample
        prefix_text = "My name is Thomas and my main"
        input_tokens = tokenizer(
            prefix_text,
            max_length=256,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
>       compiled_model = forge.compile(
            model,
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_causal_lm",
        )

forge/test/models/pytorch/text/opt/test_opt.py:42: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

context = CompileContext(modules=[Module pt_opt_350m_causal_lm], graph_name='pt_opt_350m_causal_lm', compiler_cfg=CompilerConfig...in_recompile=False, recompile_count=0, target_cycles_offset=0, forge_module=None, compiled_binary=None, attach_to=None)

    def run_optimization_pass(context: CompileContext) -> CompileDepth:
        """
        Runs optimization passes.
    
        Parameters
        ----------
        context: CompileContext
            Compile context
    
        Returns
        -------
        CompileDepth - next compile stage
        """
        compiler_cfg = context.compiler_cfg
        graph_name = context.graph_name
        graph, intermediate_tensors = context.graph, context.intermediate_tensors
    
>       run_optimization_graph_passes(graph)
E       RuntimeError: TT_ASSERT @ /__w/tt-forge-fe/tt-forge-fe/forge/csrc/passes/commute_utils.cpp:1105: reshape->op_name() == "reshape"
E       info:
E       update_reshape_attr called for a non-reshape operation
E       backtrace:
E        --- tt::passes::update_reshape_attr(tt::graphlib::OpNode*, tt::graphlib::Shape)
E        --- tt::passes::commute_and_bypass(tt::graphlib::Graph*, std::vector<tt::graphlib::Node*, std::allocator<tt::graphlib::Node*> > const&)
E        --- tt::passes::erase_inverse_ops(tt::graphlib::Graph*)
E        --- tt::run_optimization_graph_passes(tt::graphlib::Graph*)
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xfc649) [0x7f1800a55649]
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xdf905) [0x7f1800a38905]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x18b282) [0x5618e4ac0282]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x5c7d) [0x5618e4aaff4d]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0x122) [0x5618e4ace882]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x818) [0x5618e4aaaae8]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0xbb) [0x5618e4ace81b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]

forge/forge/compile.py:785: RuntimeError

variant = 'facebook/opt-1.3b', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_opt_causal_lm(variant, test_device):
        # Load tokenizer and model from HuggingFace
        # Variants: "facebook/opt-125m", "facebook/opt-350m", "facebook/opt-1.3b"
    
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        config = OPTConfig.from_pretrained(variant)
        config_dict = config.to_dict()
        config_dict["return_dict"] = False
        config_dict["use_cache"] = False
        config = OPTConfig(**config_dict)
        model = download_model(OPTForCausalLM.from_pretrained, variant, config=config)
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
    
        # Input sample
        prefix_text = "My name is Thomas and my main"
        input_tokens = tokenizer(
            prefix_text,
            max_length=256,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
>       compiled_model = forge.compile(
            model,
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_causal_lm",
        )

forge/test/models/pytorch/text/opt/test_opt.py:42: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

context = CompileContext(modules=[Module pt_opt_1_3b_causal_lm], graph_name='pt_opt_1_3b_causal_lm', compiler_cfg=CompilerConfig...in_recompile=False, recompile_count=0, target_cycles_offset=0, forge_module=None, compiled_binary=None, attach_to=None)

    def run_optimization_pass(context: CompileContext) -> CompileDepth:
        """
        Runs optimization passes.
    
        Parameters
        ----------
        context: CompileContext
            Compile context
    
        Returns
        -------
        CompileDepth - next compile stage
        """
        compiler_cfg = context.compiler_cfg
        graph_name = context.graph_name
        graph, intermediate_tensors = context.graph, context.intermediate_tensors
    
>       run_optimization_graph_passes(graph)
E       RuntimeError: TT_ASSERT @ /__w/tt-forge-fe/tt-forge-fe/forge/csrc/passes/commute_utils.cpp:1105: reshape->op_name() == "reshape"
E       info:
E       update_reshape_attr called for a non-reshape operation
E       backtrace:
E        --- tt::passes::update_reshape_attr(tt::graphlib::OpNode*, tt::graphlib::Shape)
E        --- tt::passes::commute_and_bypass(tt::graphlib::Graph*, std::vector<tt::graphlib::Node*, std::allocator<tt::graphlib::Node*> > const&)
E        --- tt::passes::erase_inverse_ops(tt::graphlib::Graph*)
E        --- tt::run_optimization_graph_passes(tt::graphlib::Graph*)
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xfc649) [0x7f1800a55649]
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xdf905) [0x7f1800a38905]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x18b282) [0x5618e4ac0282]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x5c7d) [0x5618e4aaff4d]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0x122) [0x5618e4ace882]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x818) [0x5618e4aaaae8]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0xbb) [0x5618e4ace81b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]

forge/forge/compile.py:785: RuntimeError

variant = 'facebook/opt-125m', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_opt_qa(variant, test_device):
        # Load tokenizer and model from HuggingFace
        # Variants: "facebook/opt-125m", "facebook/opt-350m", "facebook/opt-1.3b"
        # NOTE: These model variants are pre-trined only. They need to be fine-tuned
        # on a downstream task. Code is for demonstration purposes only.
    
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        model = download_model(OPTForQuestionAnswering.from_pretrained, variant, torchscript=True)
    
        # Load data sample
        question, context = "Who was Jim Henson?", "Jim Henson was a nice puppet"
    
        # Data preprocessing
        input_tokens = tokenizer(
            question,
            context,
            max_length=32,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
>       compiled_model = forge.compile(
            model,
            sample_inputs=inputs,
            module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_")) + "_qa",
        )

forge/test/models/pytorch/text/opt/test_opt.py:78: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

context = CompileContext(modules=[Module pt_opt_125m_qa], graph_name='pt_opt_125m_qa', compiler_cfg=CompilerConfig(enable_traini...in_recompile=False, recompile_count=0, target_cycles_offset=0, forge_module=None, compiled_binary=None, attach_to=None)

    def run_optimization_pass(context: CompileContext) -> CompileDepth:
        """
        Runs optimization passes.
    
        Parameters
        ----------
        context: CompileContext
            Compile context
    
        Returns
        -------
        CompileDepth - next compile stage
        """
        compiler_cfg = context.compiler_cfg
        graph_name = context.graph_name
        graph, intermediate_tensors = context.graph, context.intermediate_tensors
    
>       run_optimization_graph_passes(graph)
E       RuntimeError: TT_ASSERT @ /__w/tt-forge-fe/tt-forge-fe/forge/csrc/passes/commute_utils.cpp:1105: reshape->op_name() == "reshape"
E       info:
E       update_reshape_attr called for a non-reshape operation
E       backtrace:
E        --- tt::passes::update_reshape_attr(tt::graphlib::OpNode*, tt::graphlib::Shape)
E        --- tt::passes::commute_and_bypass(tt::graphlib::Graph*, std::vector<tt::graphlib::Node*, std::allocator<tt::graphlib::Node*> > const&)
E        --- tt::passes::erase_inverse_ops(tt::graphlib::Graph*)
E        --- tt::run_optimization_graph_passes(tt::graphlib::Graph*)
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xfc649) [0x7f1800a55649]
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xdf905) [0x7f1800a38905]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x18b282) [0x5618e4ac0282]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x5c7d) [0x5618e4aaff4d]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0x122) [0x5618e4ace882]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x818) [0x5618e4aaaae8]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0xbb) [0x5618e4ace81b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]

forge/forge/compile.py:785: RuntimeError

variant = 'microsoft/phi-3-mini-4k-instruct', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants)
    def test_phi3_causal_lm(variant, test_device):
    
        # Configurations
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        # Phi3Config from pretrained variant, disable return_dict and caching.
        config = Phi3Config.from_pretrained(variant)
        config_dict = config.to_dict()
        config_dict["return_dict"] = False
        config_dict["use_cache"] = False
        config = Phi3Config(**config_dict)
    
        # Load tokenizer and model from HuggingFace
        tokenizer = AutoTokenizer.from_pretrained(variant, return_tensors="pt", trust_remote_code=True)
        tokenizer.add_special_tokens({"pad_token": "[PAD]"})
    
        model = Phi3ForCausalLM.from_pretrained(variant, trust_remote_code=True, config=config)
        model.eval()
    
        # input_prompt
        input_prompt = "Africa is an emerging economy because"
    
        # Tokenize input
        inputs = tokenizer(
            input_prompt,
            return_tensors="pt",
            max_length=256,
            pad_to_max_length=True,
            truncation=True,
        )
    
        input_ids = inputs["input_ids"]
        attn_mask = inputs["attention_mask"]
    
        inputs = [input_ids, attn_mask]
    
>       compiled_model = forge.compile(
            model, sample_inputs=inputs, module_name="pt_" + str(variant.split("/")[-1].replace("-", "_")) + "_causal_lm"
        )

forge/test/models/pytorch/text/phi3/test_phi3.py:59: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
forge/forge/compile.py:634: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
forge/forge/compile.py:973: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
forge/forge/tvm_to_python.py:2076: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
forge/forge/tvm_to_python.py:2168: in compile_tvm_to_python
    json_graphs, flattened_pytorch_inputs, weights = load_tvm_graph(
third_party/tvm/python/tvm/contrib/forge_compile.py:106: in load_tvm_graph
    json_graphs, flattened_inputs = compile_tvm_graph(inputs, module, compiler_cfg, graph_name=graph_name, input_names=input_names, path=path, verify_cfg=verify_cfg, framework=framework)
third_party/tvm/python/tvm/contrib/forge_compile.py:146: in compile_tvm_graph
    json_graphs, inputs = compile_pytorch_for_forge(module, *inputs, graph_name=graph_name, compiler_cfg=compiler_cfg, verify_cfg=verify_cfg, input_names=input_names)
third_party/tvm/python/tvm/contrib/forge_compile.py:372: in compile_pytorch_for_forge
    mod, params = tvm.relay.frontend.from_pytorch(traced_model, input_structure, do_convert_params=convert_params)
third_party/tvm/python/tvm/relay/frontend/pytorch.py:6077: in from_pytorch
    converter.report_missing_conversion(op_names)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tvm.relay.frontend.pytorch.PyTorchOpConverter object at 0x7f18f02dea40>
op_names = {'aten::Int', 'aten::ScalarImplicit', 'aten::add', 'aten::add_', 'aten::arange', 'aten::bitwise_or_', ...}

    def report_missing_conversion(self, op_names):
        """Check if all ops in an input graph are supported by TVM"""
        known_ops = [
            "prim::Constant",
            "prim::GetAttr",
            "prim::ListConstruct",
            "prim::ListUnpack",
            "prim::TupleConstruct",
            "prim::TupleUnpack",
            "prim::RaiseException",
            "prim::If",
            "prim::Loop",
            "prim::DictConstruct",
            "prim::dtype",
            "prim::SetAttr",
            "prim::unchecked_cast"
        ]
        known_ops += list(self.convert_map.keys())
        known_ops += list(qnn_torch.convert_map.keys())
    
        missing = []
    
        for op_name in op_names:
            # Also take care of in-place variant ops like aten::relu_
            if op_name not in known_ops and not (
                op_name.endswith("_") and op_name[:-1] in known_ops
            ):
                missing.append(op_name)
    
        if missing:
            msg = f"The following operators are not implemented: {missing}"
>           raise NotImplementedError(msg)
E           NotImplementedError: The following operators are not implemented: ['aten::bitwise_or_']

third_party/tvm/python/tvm/relay/frontend/pytorch.py:4956: NotImplementedError

variant = 'facebook/xglm-1.7B', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_xglm_causal_lm(variant, test_device):
        # Set Forge configuration parameters
        compiler_cfg = forge.config._get_global_compiler_config()
        compiler_cfg.compile_depth = forge.CompileDepth.SPLIT_GRAPH
    
        config = XGLMConfig.from_pretrained(variant)
        config_dict = config.to_dict()
        config_dict["return_dict"] = False
        config_dict["use_cache"] = False
        config = XGLMConfig(**config_dict)
        model = download_model(XGLMForCausalLM.from_pretrained, variant, config=config)
        tokenizer = download_model(AutoTokenizer.from_pretrained, variant)
        tokenizer.pad_token = tokenizer.eos_token
    
        # Input sample
        prefix_text = "My name is Thomas and my main"
        input_tokens = tokenizer(
            prefix_text,
            max_length=256,
            padding="max_length",
            truncation=True,
            return_tensors="pt",
        )
    
        inputs = [input_tokens["input_ids"], input_tokens["attention_mask"]]
>       compiled_model = forge.compile(
            model, sample_inputs=inputs, module_name="pt_" + str(variant.split("/")[-1].replace("-", "_").replace(".", "_"))
        )

forge/test/models/pytorch/text/xglm/test_xglm.py:41: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

context = CompileContext(modules=[Module pt_xglm_1_7B], graph_name='pt_xglm_1_7B', compiler_cfg=CompilerConfig(enable_training=F...in_recompile=False, recompile_count=0, target_cycles_offset=0, forge_module=None, compiled_binary=None, attach_to=None)

    def run_optimization_pass(context: CompileContext) -> CompileDepth:
        """
        Runs optimization passes.
    
        Parameters
        ----------
        context: CompileContext
            Compile context
    
        Returns
        -------
        CompileDepth - next compile stage
        """
        compiler_cfg = context.compiler_cfg
        graph_name = context.graph_name
        graph, intermediate_tensors = context.graph, context.intermediate_tensors
    
>       run_optimization_graph_passes(graph)
E       RuntimeError: TT_ASSERT @ /__w/tt-forge-fe/tt-forge-fe/forge/csrc/passes/commute_utils.cpp:1105: reshape->op_name() == "reshape"
E       info:
E       update_reshape_attr called for a non-reshape operation
E       backtrace:
E        --- tt::passes::update_reshape_attr(tt::graphlib::OpNode*, tt::graphlib::Shape)
E        --- tt::passes::commute_and_bypass(tt::graphlib::Graph*, std::vector<tt::graphlib::Node*, std::allocator<tt::graphlib::Node*> > const&)
E        --- tt::passes::erase_inverse_ops(tt::graphlib::Graph*)
E        --- tt::run_optimization_graph_passes(tt::graphlib::Graph*)
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xfc649) [0x7f1800a55649]
E        --- /__w/tt-forge-fe/tt-forge-fe/forge/forge/_C.so(+0xdf905) [0x7f1800a38905]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x18b282) [0x5618e4ac0282]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x5c7d) [0x5618e4aaff4d]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0x122) [0x5618e4ace882]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x818) [0x5618e4aaaae8]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(PyObject_Call+0xbb) [0x5618e4ace81b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_FastCallDictTstate+0x16d) [0x5618e4ab5dbd]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_Call_Prepend+0x5c) [0x5618e4acad4c]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x29e054) [0x5618e4bd3054]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyObject_MakeTpCall+0x25b) [0x5618e4ab6b4b]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x671a) [0x5618e4ab09ea]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x6d2) [0x5618e4aaa9a2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x2c89) [0x5618e4aacf59]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x1a22) [0x5618e4aabcf2]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyFunction_Vectorcall+0x7c) [0x5618e4ac0aec]
E        --- /opt/ttforge-toolchain/venv/bin/python(_PyEval_EvalFrameDefault+0x58aa) [0x5618e4aafb7a]
E        --- /opt/ttforge-toolchain/venv/bin/python(+0x198be1) [0x5618e4acdbe1]

forge/forge/compile.py:785: RuntimeError

test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    # @pytest.mark.xfail(reason="Failing with pcc=0.82")
    def test_nbeats_with_seasonality_basis(test_device):
        compiler_cfg = forge.config._get_global_compiler_config()
    
        x, x_mask = get_electricity_dataset_input()
    
        pytorch_model = NBeatsWithSeasonalityBasis(
            input_size=72,
            output_size=24,
            num_of_harmonics=1,
            stacks=30,
            layers=4,
            layer_size=2048,
        )
        pytorch_model.eval()
        compiled_model = forge.compile(pytorch_model, sample_inputs=[x, x_mask], module_name="nbeats_seasonality")
        inputs = [x, x_mask]
>       co_out = compiled_model(*inputs)

forge/test/models/pytorch/timeseries/nbeats/test_nbeats.py:38: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <forge.compiled_graph_state.CompiledModel object at 0x7f18394a7340>
inputs = (tensor([[[[ 160.50679,  156.32184,  146.39499,  ...,  264.03345,  169.91641,  163.64682],
          [  79.53951,   85...[1., 1., 1.,  ..., 1., 1., 1.],
          [1., 1., 1.,  ..., 1., 1., 1.],
          [1., 1., 1.,  ..., 1., 1., 1.]]]]))
inputs_and_parameters = [tensor([[[[ 160.50679,  156.32184,  146.39499,  ...,  264.03345,  169.91641,  163.64682],
          [  79.53951,   85...0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]]), ...]

    def __call__(self, *inputs: AnyTensor) -> List[torch.Tensor]:
        """
        Run inference on the compiled model.
    
        Parameters
        ----------
        inputs: [Tensor, ...]
            Input tensors
    
        Returns
        -------
        List[Tensor]
            Output tensors
        """
        self.inputs = [*inputs]
        inputs_and_parameters = [
            *inputs,
            *self.fwd_compiled_graph_state.get_ordered_constant_tensors(),
            *self.fwd_compiled_graph_state.get_ordered_parameter_tensors(),
        ]
    
        if any([not isinstance(t, torch.Tensor) for t in inputs_and_parameters]):
            logger.info("Converting inputs and parameters to PyTorch tensors...")
            inputs_and_parameters = to_pt_tensors(inputs_and_parameters)
    
        if self.training() and isinstance(self.framework_module, PyTorchModule):
            for name, param in self.framework_module.module.named_parameters():
                if param.requires_grad:
                    our_tensor = self.fwd_compiled_graph_state.get_parameter_tensor(name)
    
                    # NOTE: for parameters that require gradients, we want to share the same tensor with the PyTorch module.
                    # This is because we want to be able to optimize the parameters both on the device (through our runtime)
                    # and via the torch optimizers. So this ensures that whichever side updates the parameter value, the other side can see the change.
                    #
                    # This could change in the future, but for now ensure that our premise is correct.
                    assert param is our_tensor
    
        logger.info(
            f"Running model {self.framework_module.get_name()} {self.fwd_compiled_graph_state.graph.get_name()} on device..."
        )
>       all_outputs = run_binary(self.compiled_binary, int(ProgramId.FORWARD), inputs_and_parameters)
E       RuntimeError: Tensor 4 - stride mismatch: expected [24, 1], got [1, 12]

forge/forge/compiled_graph_state.py:273: RuntimeError

variant = 'ese_vovnet39b', test_device = None

    @pytest.mark.nightly
    @pytest.mark.model_analysis
    @pytest.mark.parametrize("variant", variants, ids=variants)
    def test_vovnet_timm_pytorch(variant, test_device):
        model, inputs, _ = generate_model_vovnet_imgcls_timm_pytorch(
            test_device,
            variant,
        )
>       compiled_model = forge.compile(model, sample_inputs=[inputs[0]], module_name=f"pt_{variant}")

forge/test/models/pytorch/vision/vovnet/test_vovnet.py:104: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
forge/forge/compile.py:250: in compile_main
    return forge_compile_from_context(compile_context)
forge/forge/compile.py:292: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
forge/forge/compile.py:785: in run_optimization_pass
    run_optimization_graph_passes(graph)
forge/forge/op/eval/forge/__init__.py:217: in <lambda>
    return lambda *inputs: module_or_class.shape(op_type.op, op_type.attr, *inputs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

type = 'multiply', attr = [], ops = [[1, 1, 7, 7168], [1, 1, 7, 7]]

    def shape(type, attr, ops) -> Tuple[Tuple, List]:
        assert len(ops) == 2, "Eltwise binary should have two inputs"
    
        if type == "binary_stack":
            dim = attr[0]
            assert ops[0] == ops[1]
            output_shape = list(ops[0])
            output_shape[dim] *= 2
            return tuple(output_shape), []
    
        assert len(attr) == 0, "Eltwise binary should have no attributes"
    
        broadcast = []
        output_shape = []
    
        ops[0] = list(ops[0])
        while len(ops[0]) < len(ops[1]):
            ops[0] = [1] + ops[0]
    
        ops[1] = list(ops[1])
        while len(ops[1]) < len(ops[0]):
            ops[1] = [1] + ops[1]
    
        for dim in range(len(ops[0])):
            if ops[0][dim] != ops[1][dim]:
                if ops[1][dim] == 1:
                    broadcast.append((1, dim - len(ops[1]), ops[0][dim]))  # Convert to negative indexing
                    output_shape.append(ops[0][dim])
                else:
                    assert (
>                       ops[0][dim] == 1
                    ), f"Eltwise binary ops must have the same shape in both inputs, or one operand must be 1 wide to broadcast: {ops[0]} vs {ops[1]}"
E                   AssertionError: Eltwise binary ops must have the same shape in both inputs, or one operand must be 1 wide to broadcast: [1, 1, 7, 7168] vs [1, 1, 7, 7]

forge/forge/op/eval/forge/eltwise_binary.py:91: AssertionError