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ai: fix 'nother crash' name ConvNeXt submodels
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b2a320134e
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8bdded23eb
2 changed files with 10 additions and 5 deletions
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@ -47,10 +47,10 @@ class LayerContrastiveEncoder(tf.keras.layers.Layer):
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config["feature_dim"] = self.param_feature_dim
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return config
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def build(self, input_shape):
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# print("LAYER:build input_shape", input_shape)
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super().build(input_shape=input_shape[0])
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self.embedding.build(input_shape=tf.TensorShape([ *self.embedding_input_shape ]))
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# def build(self, input_shape):
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# # print("LAYER:build input_shape", input_shape)
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# super().build(input_shape=input_shape[0])
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# self.embedding.build(input_shape=tf.TensorShape([ *self.embedding_input_shape ]))
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def call(self, input_thing):
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result = self.encoder(input_thing)
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@ -21,6 +21,8 @@ depths_dims = dict(
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convnext_xlarge = (dict(depths=[3, 3, 27, 3], dims=[256, 512, 1024, 2048])),
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)
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next_model_number = 0
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def make_convnext(input_shape, arch_name="convnext_tiny", **kwargs):
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"""Makes a ConvNeXt model.
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Returns a tf.keras.Model.
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@ -32,10 +34,13 @@ def make_convnext(input_shape, arch_name="convnext_tiny", **kwargs):
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shape = input_shape
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)
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layer_out = convnext(layer_in, **depths_dims[arch_name], **kwargs)
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return tf.keras.Model(
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result = tf.keras.Model(
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name=f"convnext{next_model_number}",
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inputs = layer_in,
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outputs = layer_out
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)
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next_model_number += 1
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return result
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def convnext(
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