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Fix position encoder in examples/.../token_learner.py #727

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merged 2 commits into from
Aug 15, 2023
Merged

Fix position encoder in examples/.../token_learner.py #727

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8f0c8bc
position encoding token_learner
guillaumebaquiast Aug 13, 2023
f6dcbfd
Merge branch 'main' into position-encoder-token-learner
guillaumebaquiast Aug 15, 2023
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34 changes: 21 additions & 13 deletions examples/keras_io/vision/token_learner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
Authors: [Aritra Roy Gosthipaty](https://twitter.com/ariG23498), [Sayak Paul](https://twitter.com/RisingSayak) (equal contribution)
Converted to Keras Core by: [Muhammad Anas Raza](https://anasrz.com)
Date created: 2021/12/10
Last modified: 2023/07/18
Last modified: 2023/08/14
Description: Adaptively generating a smaller number of tokens for Vision Transformers.
Accelerator: GPU
"""
Expand Down Expand Up @@ -165,19 +165,25 @@
"""


def position_embedding(
projected_patches, num_patches=NUM_PATCHES, projection_dim=PROJECTION_DIM
):
# Build the positions.
positions = ops.arange(start=0, stop=num_patches, step=1)
class PatchEncoder(layers.Layer):
def __init__(self, num_patches, projection_dim):
super().__init__()
self.num_patches = num_patches
self.position_embedding = layers.Embedding(
input_dim=num_patches, output_dim=projection_dim
)

# Encode the positions with an Embedding layer.
encoded_positions = layers.Embedding(
input_dim=num_patches, output_dim=projection_dim
)(positions)
def call(self, patch):
positions = ops.expand_dims(
ops.arange(start=0, stop=self.num_patches, step=1), axis=0
)
encoded = patch + self.position_embedding(positions)
return encoded

# Add encoded positions to the projected patches.
return projected_patches + encoded_positions
def get_config(self):
config = super().get_config()
config.update({"num_patches": self.num_patches})
return config


"""
Expand Down Expand Up @@ -337,7 +343,9 @@ def create_vit_classifier(
) # (B, number_patches, projection_dim)

# Add positional embeddings to the projected patches.
encoded_patches = position_embedding(
encoded_patches = PatchEncoder(
num_patches=NUM_PATCHES, projection_dim=PROJECTION_DIM
)(
projected_patches
) # (B, number_patches, projection_dim)
encoded_patches = layers.Dropout(0.1)(encoded_patches)
Expand Down