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https://github.com/sbrl/research-rainfallradar
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ai Bugfix LayerContrastiveEncoder: channels → input_channels
for consistency
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2 changed files with 10 additions and 10 deletions
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@ -7,7 +7,7 @@ from .convnext import make_convnext
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class LayerContrastiveEncoder(tf.keras.layers.Layer):
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def __init__(self, input_width, input_height, channels, arch_name="convnext_tiny", summary_file=None, feature_dim=2048, **kwargs):
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def __init__(self, input_width, input_height, input_channels, arch_name="convnext_tiny", summary_file=None, feature_dim=2048, **kwargs):
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"""Creates a new contrastive learning encoder layer.
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Note that the input format MUST be channels_last. This is because Tensorflow/Keras' Dense layer does NOT support specifying an axis. Go complain to them, not me.
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While this is intended for contrastive learning, this can (in theory) be used anywhere as it's just a generic wrapper layer.
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@ -24,18 +24,18 @@ class LayerContrastiveEncoder(tf.keras.layers.Layer):
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print(f"input_width: {input_width}")
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print(f"input_height: {input_height}")
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print(f"channels: {channels}")
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print(f"channels: {input_channels}")
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self.param_input_width = input_width
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self.param_input_height = input_height
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self.param_channels = channels
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self.param_feature_dim = feature_dim
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self.param_arch_name = arch_name
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self.param_input_width = input_width
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self.param_input_height = input_height
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self.param_input_channels = input_channels
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self.param_feature_dim = feature_dim
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self.param_arch_name = arch_name
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"""The main ConvNeXt model that forms the encoder.
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"""
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self.encoder = make_convnext(
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input_shape = (self.param_input_width, self.param_input_height, self.param_channels),
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input_shape = (self.param_input_width, self.param_input_height, self.param_input_channels),
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classifier_activation = tf.nn.relu, # this is not actually a classifier, but rather a feature encoder
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num_classes = self.param_feature_dim, # size of the feature dimension, see the line above this one
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arch_name = self.param_arch_name
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@ -33,7 +33,7 @@ def model_rainfallwater_contrastive(metadata, shape_water, batch_size=64, featur
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rainfall = LayerContrastiveEncoder(
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input_width=rainfall_width,
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input_height=rainfall_height,
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channels=rainfall_channels,
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input_channels=rainfall_channels,
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feature_dim=feature_dim,
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summary_file=summary_file,
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arch_name="convnext_tiny",
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@ -42,7 +42,7 @@ def model_rainfallwater_contrastive(metadata, shape_water, batch_size=64, featur
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water = LayerContrastiveEncoder(
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input_width=water_width,
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input_height=water_height,
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channels=water_channels,
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input_channels=water_channels,
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feature_dim=feature_dim,
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arch_name="convnext_xtiny",
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summary_file=summary_file
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