Fix: fix activation and loss #12
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## main #12 +/- ##
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- Coverage 88.70% 88.44% -0.27%
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Files 6 6
Lines 248 251 +3
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+ Hits 220 222 +2
- Misses 28 29 +1 ☔ View full report in Codecov by Sentry. |
WalkthroughWalkthroughThe recent updates focused on refining various components of the CLIP model, particularly within its Vision Transformer (ViT) and GPT architectures. This involved adjustments to embedding dimensions, layer normalization, MLP structures, and loss computations. The CLIP model now features more robust temperature handling and normalization within its forward method. Additionally, tests were updated to reflect these changes. Changes
Sequence DiagramssequenceDiagram
participant User
participant ViT
participant GPT
participant CLIP
Note over User,CLIP: Data passes through different stages
User ->> ViT: Image data
ViT ->> CLIP: Extracted features
User ->> GPT: Text data
GPT ->> CLIP: Encoded text features
CLIP ->> CLIP: Normalize and compute logits
CLIP ->> User: Similarity results
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Actionable comments posted: 2
Outside diff range and nitpick comments (1)
clip/clip/model.py (1)
Line range hint
4-4: Remove Unused ImportThe import of
numpyis unused and should be removed to clean up the code.- import numpy as npTools
Ruff
11-11: Yoda conditions are discouraged, use
temperature > 0instead (SIM300)Replace Yoda condition with
temperature > 0
Review details
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Files selected for processing (5)
- clip/clip/image/vit.py (1 hunks)
- clip/clip/languange/gpt.py (4 hunks)
- clip/clip/loss.py (1 hunks)
- clip/clip/model.py (1 hunks)
- clip/tests/language/test_gpt.py (1 hunks)
Files not reviewed due to errors (1)
- clip/clip/languange/gpt.py (no review received)
Additional context used
Ruff
clip/clip/model.py
4-4:
numpyimported but unused (F401)Remove unused import:
numpy
11-11: Yoda conditions are discouraged, use
temperature > 0instead (SIM300)Replace Yoda condition with
temperature > 0
Additional comments not posted (5)
clip/clip/loss.py (2)
7-9: Constructor SimplificationThe constructor of
CLIPLosshas been simplified to only require adeviceparameter. This change makes the class more flexible and easier to use in different contexts.
15-18: Dynamic Batch Size HandlingThe update to dynamically determine the batch size based on the input tensor is a good improvement. It enhances the flexibility of the loss function to handle varying batch sizes.
clip/clip/model.py (1)
24-24: Temperature Parameter HandlingThe change to handle the temperature as a log-transformed parameter using
nn.Parameteris a clever way to ensure that the temperature remains positive and within a specific range during training.clip/clip/image/vit.py (2)
53-57: Refactor of MLP head in ViT class approvedThe new MLP head structure introduces additional layers and normalization, which are likely to improve the model's ability to learn complex patterns. However, consider adding comments to explain the design choice, especially the introduction of the intermediate layer normalization and the two-stage linear transformation.
[REFACTOR_SUGGESTion]
+ # Layer normalization is applied before the MLP layers to ensure that the features are normalized + # The MLP consists of two linear transformations with an intermediate layer normalization to enhance learning stability and performance
Line range hint
1-57: Overall architecture and initialization method of ViT class are well-implementedThe overall architecture of the ViT class, including transformer blocks and attention mechanisms, is robust. The custom weight initialization method is appropriate for the network's layers, ensuring good model convergence. No further action is needed here.
[APROVED]
| @@ -12,4 +12,4 @@ def test_GPT_forward_shape(): | |||
| dummy_txts[1, 928] = 50256 | |||
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| ecoded = gpt(dummy_txts) | |||
| assert ecoded.shape == (2, config.vocab_size) | |||
| assert ecoded.shape == (2, config.out_dim) | |||
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Typographical Error in Variable Name
The variable ecoded should be corrected to encoded to match the variable name used in the test function.
- ecoded = gpt(dummy_txts)
+ encoded = gpt(dummy_txts)Committable suggestion was skipped due to low confidence.
| @@ -8,28 +8,29 @@ class CLIP(nn.Module): | |||
| def __init__(self, txt_encoder, img_encoder, embd_dim, temperature): | |||
| super().__init__() | |||
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| assert 0 <= temperature <= 1, "temperature must be in range [0,1]" | |||
| assert 0 < temperature, "temperature must be greater than zero." | |||
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Use of Yoda Conditions
Replace the Yoda condition with a more conventional conditional expression for better readability.
- assert 0 < temperature, "temperature must be greater than zero."
+ assert temperature > 0, "Temperature must be greater than zero."Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| assert 0 < temperature, "temperature must be greater than zero." | |
| assert temperature > 0, "Temperature must be greater than zero." |
Tools
Ruff
11-11: Yoda conditions are discouraged, use
temperature > 0instead (SIM300)Replace Yoda condition with
temperature > 0
Summary by CodeRabbit
New Features
Bug Fixes
Refactor