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zK3`mae$n}<^DDKI1J#Vb&lf(h;Z~wryL2OF1#=6#*C%VKYZJxMl%Z|53U+>2UerfpRZ>I#Dg+CLOpJ;mfxv0SsKd;D_ zEFq^IxZ_#)4|XSX)xW%2`rGB^@xIiMQ#%gV@e zTE9u?@@M-!D#r2k%6Gr6{q;R3{zcCI`7c}3tM}#XU%x)wKjEfN0@(EH|5pDkxBi*W zs>~{1>EIP1<)6@S>8sE*q34Y!W}Mu;Rk5K_dBcV~o;`nlPes(TeWht1 zO>Wl3$G`t8cH!IEGs>I3?gv_M^XjYbx^wqV`(3~5y#D{{ZRd?|zkmJu?w!w(%g*QT zoqylpzyu|)W9rWwXUvKIV_2fwg)()4 j%blZyU-H97(LnT{dZ48R%!YL`3_#%N>gTe~DWM4fqv6S$ literal 0 HcmV?d00001 From bb68c8fff1b14bcc6cbc8bf9bab6dd5cbfa357a6 Mon Sep 17 00:00:00 2001 From: Awsaf Date: Mon, 11 Dec 2023 19:15:33 +0600 Subject: [PATCH 2/7] Create CITATION.cff --- CITATION.cff | 1 + 1 file changed, 1 insertion(+) create mode 100644 CITATION.cff diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/CITATION.cff @@ -0,0 +1 @@ + From 52fb4487dc8c6a1d4fbceb1d75a814b8dbfaef1f Mon Sep 17 00:00:00 2001 From: Awsaf Date: Mon, 11 Dec 2023 19:21:45 +0600 Subject: [PATCH 3/7] Update CITATION.cff --- CITATION.cff | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/CITATION.cff b/CITATION.cff index 8b13789..69c2e7e 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -1 +1,9 @@ - +cff-version: 1.2.0 +message: "If you use this software, please cite it as below." +authors: +- family-names: "Rahman" + given-names: "Md Awsafur" +title: "Tensorflow 2.0 Implementation of GCViT: Global Context Vision Transformer" +version: 1.1.5 +date-released: 2020-07-20 +url: "https://awsaf49.github.io/gcvit-tf" From cda6faec09bdffa9644f5f478b2316cff3ba3826 Mon Sep 17 00:00:00 2001 From: Awsaf Date: Sun, 24 Dec 2023 23:48:01 +0600 Subject: [PATCH 4/7] update: replace `/` with `_` for Keras 3.0 --- gcvit/layers/feature.py | 26 +++++++++++++------------- gcvit/layers/level.py | 2 +- gcvit/models/gcvit.py | 2 +- 3 files changed, 15 insertions(+), 15 deletions(-) diff --git a/gcvit/layers/feature.py b/gcvit/layers/feature.py index 8091a8c..f1eab44 100644 --- a/gcvit/layers/feature.py +++ b/gcvit/layers/feature.py @@ -67,11 +67,11 @@ def build(self, input_shape): self.avg_pool = AdaptiveAveragePooling2D(1, name="avg_pool") self.fc = [ tf.keras.layers.Dense( - int(inp * self.expansion), use_bias=False, name="fc/0" + int(inp * self.expansion), use_bias=False, name="fc_0" ), - tf.keras.layers.Activation("gelu", name="fc/1"), - tf.keras.layers.Dense(self.oup, use_bias=False, name="fc/2"), - tf.keras.layers.Activation("sigmoid", name="fc/3"), + tf.keras.layers.Activation("gelu", name="fc_1"), + tf.keras.layers.Dense(self.oup, use_bias=False, name="fc_2"), + tf.keras.layers.Activation("sigmoid", name="fc_3"), ] super().build(input_shape) @@ -111,17 +111,17 @@ def build(self, input_shape): strides=1, padding="valid", use_bias=False, - name="conv/0", + name="conv_0", ), - tf.keras.layers.Activation("gelu", name="conv/1"), - SE(name="conv/2"), + tf.keras.layers.Activation("gelu", name="conv_1"), + SE(name="conv_2"), tf.keras.layers.Conv2D( dim, kernel_size=1, strides=1, padding="valid", use_bias=False, - name="conv/3", + name="conv_3", ), ] self.reduction = tf.keras.layers.Conv2D( @@ -179,17 +179,17 @@ def build(self, input_shape): strides=1, padding="valid", use_bias=False, - name="conv/0", + name="conv_0", ), - tf.keras.layers.Activation("gelu", name="conv/1"), - SE(name="conv/2"), + tf.keras.layers.Activation("gelu", name="conv_1"), + SE(name="conv_2"), tf.keras.layers.Conv2D( dim, kernel_size=1, strides=1, padding="valid", use_bias=False, - name="conv/3", + name="conv_3", ), ] if not self.keep_dim: @@ -237,7 +237,7 @@ def __init__(self, keep_dims=False, **kwargs): def build(self, input_shape): self.to_q_global = [ - FeatExtract(keep_dim, name=f"to_q_global/{i}") + FeatExtract(keep_dim, name=f"to_q_global_{i}") for i, keep_dim in enumerate(self.keep_dims) ] super().build(input_shape) diff --git a/gcvit/layers/level.py b/gcvit/layers/level.py index eeff7b2..abd3fbe 100644 --- a/gcvit/layers/level.py +++ b/gcvit/layers/level.py @@ -59,7 +59,7 @@ def build(self, input_shape): attn_drop=self.attn_drop, path_drop=path_drop[i], layer_scale=self.layer_scale, - name=f"blocks/{i}", + name=f"blocks_{i}", ) for i in range(self.depth) ] diff --git a/gcvit/models/gcvit.py b/gcvit/models/gcvit.py index 0b98ee1..cec382e 100644 --- a/gcvit/models/gcvit.py +++ b/gcvit/models/gcvit.py @@ -142,7 +142,7 @@ def __init__( path_drop=path_drop, layer_scale=layer_scale, resize_query=resize_query, - name=f"levels/{i}", + name=f"levels_{i}", ) self.levels.append(level) self.norm = tf.keras.layers.LayerNormalization( From a9ce1fcb4f4a3e57e1a374ce4b483e39f65bb6e5 Mon Sep 17 00:00:00 2001 From: Awsaf Date: Sun, 24 Dec 2023 23:58:23 +0600 Subject: [PATCH 5/7] fix: `name` arg bug --- gcvit/layers/attention.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/gcvit/layers/attention.py b/gcvit/layers/attention.py index 9f15deb..535e9df 100644 --- a/gcvit/layers/attention.py +++ b/gcvit/layers/attention.py @@ -33,7 +33,7 @@ def build(self, input_shape): dim * self.qkv_size, use_bias=self.qkv_bias, name="qkv" ) self.relative_position_bias_table = self.add_weight( - "relative_position_bias_table", + name="relative_position_bias_table", shape=[ (2 * self.window_size[0] - 1) * (2 * self.window_size[1] - 1), self.num_heads, From 1473a56b9a55dbd8c6ba8e4766afb2b920fc5c49 Mon Sep 17 00:00:00 2001 From: Awsaf Date: Mon, 25 Dec 2023 00:20:28 +0600 Subject: [PATCH 6/7] fix: built issue of relative index --- gcvit/layers/attention.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/gcvit/layers/attention.py b/gcvit/layers/attention.py index 535e9df..f7a7ba8 100644 --- a/gcvit/layers/attention.py +++ b/gcvit/layers/attention.py @@ -50,7 +50,7 @@ def build(self, input_shape): self.proj_dropout, name="proj_drop" ) self.softmax = tf.keras.layers.Activation("softmax", name="softmax") - self.relative_position_index = self.get_relative_position_index() + # self.relative_position_index = self.get_relative_position_index() super().build(input_shape) def get_relative_position_index(self): @@ -101,7 +101,7 @@ def call(self, inputs, **kwargs): attn = q @ tf.transpose(k, perm=[0, 1, 3, 2]) relative_position_bias = tf.gather( self.relative_position_bias_table, - tf.reshape(self.relative_position_index, shape=[-1]), + tf.reshape(self.get_relative_position_index(), shape=[-1]), ) relative_position_bias = tf.reshape( relative_position_bias, From e2176f152b8492439153d6047e42d05f05275fbf Mon Sep 17 00:00:00 2001 From: Awsaf Date: Mon, 25 Dec 2023 00:34:04 +0600 Subject: [PATCH 7/7] fix: `name` in `add_weight()` --- gcvit/layers/block.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/gcvit/layers/block.py b/gcvit/layers/block.py index 25f8a4a..dbee207 100644 --- a/gcvit/layers/block.py +++ b/gcvit/layers/block.py @@ -65,14 +65,14 @@ def build(self, input_shape): ) if self.layer_scale is not None: self.gamma1 = self.add_weight( - "gamma1", + name="gamma1", shape=[C], initializer=tf.keras.initializers.Constant(self.layer_scale), trainable=True, dtype=self.dtype, ) self.gamma2 = self.add_weight( - "gamma2", + name="gamma2", shape=[C], initializer=tf.keras.initializers.Constant(self.layer_scale), trainable=True,