Reports not found!

[aleenaelsageorge12]

I was running the sample code found on https://github.com/fastmachinelearning/hls4ml-tutorial, and the following error occurred. The spec of my setup are the following:

OS ;Ubuntu 18.04.2
Vivado hls4ml 2019.2
python 3.9

Following is the LSTM model we used.

import myutils
from datetime import datetime
import sys
import os
import pickle
from keras.models import load_model
from gensim.models import Word2Vec, KeyedVectors
from keras.preprocessing import sequence
from sklearn.metrics import accuracy_score
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.metrics import f1_score
import tensorflow as tf
import numpy

import os
import tensorflow as tf
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

import plotting
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score

import hls4ml
import numpy as np
import os

os.environ['PATH'] += os.pathsep + '/home/sh/Vivado/2019.2/bin'

#default mode / type of vulnerability
mode = "xss"

#get the vulnerability from the command line argument
if (len(sys.argv) > 1):
mode = sys.argv[1]

model = load_model('modellstm/LSTM_model_'+mode+'.h5',custom_objects={'f1_loss': myutils.f1_loss, 'f1':myutils.f1})

with open('data/' + mode + '_dataset_finaltest_X', 'rb') as fp:
FinaltestX = pickle.load(fp)
with open('data/' + mode + '_dataset_finaltest_Y', 'rb') as fp:
FinaltestY = pickle.load(fp)

now = datetime.now() # current date and time
nowformat = now.strftime("%H:%M")

#Prepare the data for the LSTM model

X_finaltest = numpy.array(FinaltestX, dtype="object")
y_finaltest = numpy.array(FinaltestY, dtype="object")

#in the original collection of data, the 0 and 1 were used the other way round, so now they are switched so that "1" means vulnerable and "0" means clean.

for i in range(len(y_finaltest)):
if y_finaltest[i] == 0:
y_finaltest[i] = 1
else:
y_finaltest[i] = 0

now = datetime.now() # current date and time
nowformat = now.strftime("%H:%M")

print(str(len(X_finaltest)) + " samples in the final test set.")

csum = 0
for y in y_finaltest:
csum = csum+y

print("percentage of vulnerable samples: " + str(int((csum / len(X_finaltest)) * 10000)/100) + "%")
print("absolute amount of vulnerable samples in test set: " + str(csum))

#padding sequences on the same length
max_length = 200
X_finaltest = sequence.pad_sequences(X_finaltest, maxlen=max_length)

X_finaltest = numpy.asarray(X_finaltest).astype(numpy.float32)
y_finaltest= numpy.asarray(y_finaltest).astype(numpy.float32)

yhat_classes = (model.predict(X_finaltest) > 0.5).astype("int32")

accuracy = accuracy_score(y_finaltest, yhat_classes)

precision = precision_score(y_finaltest, yhat_classes)
recall = recall_score(y_finaltest, yhat_classes)
F1Score = f1_score(y_finaltest, yhat_classes)

print("keras Accuracy: " + str(accuracy))
print("keras Precision: " + str(precision))
print("keras Recall: " + str(recall))
print('keras F1 score: %f' % F1Score)
print("\n")

config = hls4ml.utils.config_from_keras_model(model, granularity='model')
print("-----------------------------------")
print("Configuration")
plotting.print_dict(config)
print("-----------------------------------")
hls_model = hls4ml.converters.convert_from_keras_model(
model, hls_config=config, output_dir='model_1/hls4ml_prj', part='xcu250-figd2104-2L-e'
)

hls_model.compile()

X_finaltest = np.ascontiguousarray(X_finaltest)

y_hls = (hls_model.predict(X_finaltest) > 0.5).astype("int32")

accuracyhls = accuracy_score(y_finaltest, y_hls)

print("hls Accuracy: " + str(accuracyhls))
print("keras Accuracy: " + str(accuracy))

hls_model.build(csim=True)

hls4ml.report.read_vivado_report('model_1/hls4ml_prj/')

This is the output we get.
Why co-simulation not found?

2024-07-07 22:33:41.106293: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-07-07 22:33:41.543981: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-07-07 22:33:41.545071: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-07-07 22:33:43.163030: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
/home/sh/anaconda3/lib/python3.9/site-packages/hls4ml/converters/init.py:27: UserWarning: WARNING: Pytorch converter is not enabled!
warnings.warn("WARNING: Pytorch converter is not enabled!", stacklevel=1)
WARNING: Failed to import handlers from pooling.py: No module named 'torch'.
WARNING: Failed to import handlers from core.py: No module named 'torch'.
WARNING: Failed to import handlers from reshape.py: No module named 'torch'.
WARNING: Failed to import handlers from merge.py: No module named 'torch'.
WARNING: Failed to import handlers from convolution.py: No module named 'torch'.
8277 samples in the final test set.
percentage of vulnerable samples: 8.98%
absolute amount of vulnerable samples in test set: 744
2024-07-07 22:34:12.832143: W tensorflow/tsl/framework/cpu_allocator_impl.cc:83] Allocation of 1986480000 exceeds 10% of free system memory.
259/259 [==============================] - 23s 77ms/step
keras Accuracy: 0.9098707261084934
keras Precision: 0.49876543209876545
keras Recall: 0.543010752688172
keras F1 score: 0.519949

Interpreting Sequential
Topology:
Layer name: lstm_1_input, layer type: InputLayer, input shapes: [[None, 200, 300]], output shape: [None, 200, 300]
Layer name: lstm_1, layer type: LSTM, input shapes: [[None, 200, 300]], output shape: [None, 100]
Layer name: dense_1, layer type: Dense, input shapes: [[None, 100]], output shape: [None, 1]

Configuration
Model
Precision: fixed<16,6>
ReuseFactor: 1
Strategy: Latency
BramFactor: 1000000000
TraceOutput: False

Interpreting Sequential
Topology:
Layer name: lstm_1_input, layer type: InputLayer, input shapes: [[None, 200, 300]], output shape: [None, 200, 300]
Layer name: lstm_1, layer type: LSTM, input shapes: [[None, 200, 300]], output shape: [None, 100]
Layer name: dense_1, layer type: Dense, input shapes: [[None, 100]], output shape: [None, 1]
Creating HLS model
Writing HLS project
/home/sh/anaconda3/lib/python3.9/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via model.save(). This file format is considered legacy. We recommend using instead the native Keras format, e.g. model.save('my_model.keras').
saving_api.save_model(
Done
hls Accuracy: 0.90515887398816
keras Accuracy: 0.9098707261084934

****** Vivado(TM) HLS - High-Level Synthesis from C, C++ and SystemC v2019.2 (64-bit)
**** SW Build 2708876 on Wed Nov 6 21:39:14 MST 2019
**** IP Build 2700528 on Thu Nov 7 00:09:20 MST 2019
** Copyright 1986-2019 Xilinx, Inc. All Rights Reserved.

source /home/sh/Vivado/2019.2/scripts/vivado_hls/hls.tcl -notrace
INFO: [HLS 200-10] Running '/home/sh/Vivado/2019.2/bin/unwrapped/lnx64.o/vivado_hls'
INFO: [HLS 200-10] For user 'sh' on host 'sh-VirtualBox' (Linux_x86_64 version 5.4.0-150-generic) on Sun Jul 07 23:33:18 CEST 2024
INFO: [HLS 200-10] On os Ubuntu 18.04.6 LTS
INFO: [HLS 200-10] In directory '/home/sh/model_1/hls4ml_prj'
Sourcing Tcl script 'build_prj.tcl'
INFO: [HLS 200-10] Opening project '/home/sh/model_1/hls4ml_prj/myproject_prj'.
INFO: [HLS 200-10] Adding design file 'firmware/myproject.cpp' to the project
INFO: [HLS 200-10] Adding test bench file 'myproject_test.cpp' to the project
INFO: [HLS 200-10] Adding test bench file 'firmware/weights' to the project
INFO: [HLS 200-10] Adding test bench file 'tb_data' to the project
INFO: [HLS 200-10] Opening solution '/home/sh/model_1/hls4ml_prj/myproject_prj/solution1'.
INFO: [SYN 201-201] Setting up clock 'default' with a period of 5ns.
INFO: [SYN 201-201] Setting up clock 'default' with an uncertainty of 0.625ns.
INFO: [HLS 200-10] Setting target device to 'xcu250-figd2104-2L-e'
INFO: [XFORM 203-101] Allowed max sub elements number after partition is 4096.
INFO: [XFORM 203-1161] The maximum of name length is set into 80.
INFO: [XFORM 203-101] Allowed max sub elements number after partition is 4096.
INFO: [XFORM 203-1161] The maximum of name length is set into 80.
***** C/RTL SYNTHESIS *****
INFO: [SCHED 204-61] Option 'relax_ii_for_timing' is enabled, will increase II to preserve clock frequency constraints.
INFO: [HLS 200-10] Analyzing design file 'firmware/myproject.cpp' ...
INFO: [HLS 200-10] Analyzing design file 'firmware/myproject_axi.cpp' ...
INFO: [HLS 200-111] Finished Linking Time (s): cpu = 00:01:15 ; elapsed = 00:01:24 . Memory (MB): peak = 908.145 ; gain = 459.035 ; free physical = 584 ; free virtual = 1714
INFO: [HLS 200-111] Finished Checking Pragmas Time (s): cpu = 00:01:15 ; elapsed = 00:01:24 . Memory (MB): peak = 908.145 ; gain = 459.035 ; free physical = 584 ; free virtual = 1714
INFO: [HLS 200-10] Starting code transformations ...
INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_1>' (firmware/nnet_utils/nnet_dense_latency.h:42).
INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_2>' (firmware/nnet_utils/nnet_dense_latency.h:42).
INFO: [XFORM 203-603] Inlining function 'nnet::product::mult<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0> >::product' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' (firmware/nnet_utils/nnet_dense_latency.h:42).
INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_1>' into 'nnet::lstm_static<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:149).
INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_2>' into 'nnet::lstm_static<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:150).
INFO: [XFORM 203-603] Inlining function 'nnet::dense<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' into 'myproject' (firmware/myproject.cpp:43).
INFO: [HLS 200-111] Finished Standard Transforms Time (s): cpu = 00:10:17 ; elapsed = 00:10:40 . Memory (MB): peak = 1644.148 ; gain = 1195.039 ; free physical = 155 ; free virtual = 994
INFO: [HLS 200-10] Checking synthesizability ...
INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_1>' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_1>' (firmware/nnet_utils/nnet_dense_latency.h:66) automatically.
INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_2>' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_2>' (firmware/nnet_utils/nnet_dense_latency.h:66) automatically.
INFO: [XFORM 203-602] Inlining function 'nnet::activation::sigmoid<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, sigmoid_config2_recr>::activation' into 'nnet::lstm_static<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:166) automatically.
INFO: [XFORM 203-602] Inlining function 'nnet::activation::tanh<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, tanh_config2>::activation' into 'nnet::lstm_static<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:170) automatically.
INFO: [XFORM 203-602] Inlining function 'nnet::cast<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' into 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' (firmware/nnet_utils/nnet_dense_latency.h:66) automatically.
INFO: [HLS 200-111] Finished Checking Synthesizability Time (s): cpu = 00:10:19 ; elapsed = 00:10:42 . Memory (MB): peak = 1644.148 ; gain = 1195.039 ; free physical = 152 ; free virtual = 994
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' (firmware/nnet_utils/nnet_dense_latency.h:13:43).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::lstm_stack<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:199:45).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::lstm_static<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' (firmware/nnet_utils/nnet_recurrent.h:41:50).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::tanh<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, tanh_config2>' (firmware/nnet_utils/nnet_activation.h:427:43).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::sigmoid<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, sigmoid_config2_recr>' (firmware/nnet_utils/nnet_activation.h:109:43).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_2>' (firmware/nnet_utils/nnet_dense_latency.h:17:48).
INFO: [XFORM 203-502] Unrolling all loops for pipelining in function 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_1>' (firmware/nnet_utils/nnet_dense_latency.h:17:48).
INFO: [HLS 200-489] Unrolling loop 'Product1' (firmware/nnet_utils/nnet_dense_latency.h:37) in function 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' completely with a factor of 100.
INFO: [HLS 200-489] Unrolling loop 'Accum1' (firmware/nnet_utils/nnet_dense_latency.h:54) in function 'nnet::dense_latency<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config3>' completely with a factor of 100.
INFO: [HLS 200-489] Unrolling loop 'Loop-1' (firmware/nnet_utils/nnet_recurrent.h:205) in function 'nnet::lstm_stack<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 100.
INFO: [HLS 200-489] Unrolling loop 'Loop-2' (firmware/nnet_utils/nnet_recurrent.h:210) in function 'nnet::lstm_stack<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' completely with a factor of 200.
ERROR: [XFORM 203-504] Stop unrolling loop 'Loop-2' (firmware/nnet_utils/nnet_recurrent.h:210) in function 'nnet::lstm_stack<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2>' because it may cause large runtime and excessive memory usage due to increase in code size. Please avoid unrolling the loop or form sub-functions for code in the loop body.
ERROR: [HLS 200-70] Pre-synthesis failed.
command 'ap_source' returned error code
while executing
"source build_prj.tcl"
("uplevel" body line 1)
invoked from within
"uplevel #0 [list source $arg] "

INFO: [Common 17-206] Exiting vivado_hls at Sun Jul 7 23:44:02 2024...
CSynthesis report not found.
Vivado synthesis report not found.
Cosim report not found.
Timing report not found.
Found 1 solution(s) in model_1/hls4ml_prj//myproject_prj.
Reports for solution "solution1":

C SIMULATION RESULT:
INFO: [SIM 2] *************** CSIM start ***************
INFO: [SIM 4] CSIM will launch GCC as the compiler.
Compiling ../../../../myproject_test.cpp in debug mode
Compiling ../../../../firmware/myproject.cpp in debug mode
Compiling ../../../../firmware/myproject_axi.cpp in debug mode
Generating csim.exe
INFO: Unable to open input/predictions file, using default input.
0.000976563
INFO: Saved inference results to file: tb_data/csim_results.log
INFO: [SIM 1] CSim done with 0 errors.
INFO: [SIM 3] *************** CSIM finish ***************

Synthesis report not found.
Co-simulation report not found.

[vloncar]

Why co-simulation not found?
Because you didn't run co-sim. Check the paramters of the hls_model.build().

As for the second error, your model is simply too large.