hunk.code_window:     with set_scriptable(True):
           model = create_model(model_name, pretrained=False)
       model.eval()
       input_size = _get_input_size(model, TARGET_JIT_SIZE)
       if max(input_size) > MAX_JIT_SIZE:  # NOTE using MAX_FWD_SIZE as the final limit is intentional
           pytest.skip("Fixed input size model > limit.")
       model = torch.jit.script(model)
       outputs = model(torch.randn((batch_size, *input_size)))
       assert outputs.shape[0] == batch_size
       assert not torch.isnan(outputs).any(), 'Output included NaNs'
  
hunk.labels: keep keep keep keep replace replace replace replace keep keep keep keep keep
hunk.file_path: tests/test_models.py
hunk.type: replace
file: # Xception
  
  **Xception** is a convolutional neural network architecture that relies solely on [depthwise separable convolution layers](https://paperswithcode.com/method/depthwise-separable-convolution).
  
  The weights from this model were ported from [Tensorflow/Models](https://github.com/tensorflow/models).
  
  {% include 'code_snippets.md' %}
  
  ## How do I train this model?
  
  You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
  
  ## Citation
  
  ```BibTeX
  @article{DBLP:journals/corr/ZagoruykoK16,
  @misc{chollet2017xception,
        title={Xception: Deep Learning with Depthwise Separable Convolutions}, 
        author={François Chollet},
        year={2017},
        eprint={1610.02357},
        archivePrefix={arXiv},
        primaryClass={cs.CV}
  }
  ```
  
  <!--
  Type: model-index
  Collections:
  - Name: Xception
    Paper:
      Title: 'Xception: Deep Learning with Depthwise Separable Convolutions'
      URL: https://paperswithcode.com/paper/xception-deep-learning-with-depthwise
  Models:
  - Name: xception
    In Collection: Xception
    Metadata:
      FLOPs: 10600506792
      Parameters: 22860000
      File Size: 91675053
      Architecture:
      - 1x1 Convolution
      - Convolution
      - Dense Connections
      - Depthwise Separable Convolution
      - Global Average Pooling
      - Max Pooling
      - ReLU
      - Residual Connection
      - Softmax
      Tasks:
      - Image Classification
      Training Data:
      - ImageNet
      ID: xception
      Crop Pct: '0.897'
      Image Size: '299'
      Interpolation: bicubic
    Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/xception.py#L229
    Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-cadene/xception-43020ad28.pth
    Results:
    - Task: Image Classification
      Dataset: ImageNet
      Metrics:
        Top 1 Accuracy: 79.05%
        Top 5 Accuracy: 94.4%
  - Name: xception41
    In Collection: Xception
    Metadata:
      FLOPs: 11681983232
      Parameters: 26970000
      File Size: 108422028
      Architecture:
      - 1x1 Convolution
      - Convolution
      - Dense Connections
      - Depthwise Separable Convolution
      - Global Average Pooling
      - Max Pooling
      - ReLU
      - Residual Connection
      - Softmax
      Tasks:
      - Image Classification
      Training Data:
      - ImageNet
      ID: xception41
      Crop Pct: '0.903'
      Image Size: '299'
      Interpolation: bicubic
    Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/xception_aligned.py#L181
    Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_41-e6439c97.pth
    Results:
    - Task: Image Classification
      Dataset: ImageNet
      Metrics:
        Top 1 Accuracy: 78.54%
        Top 5 Accuracy: 94.28%
  - Name: xception65
    In Collection: Xception
    Metadata:
      FLOPs: 17585702144
      Parameters: 39920000
      File Size: 160536780
      Architecture:
      - 1x1 Convolution
      - Convolution
      - Dense Connections
      - Depthwise Separable Convolution
      - Global Average Pooling
      - Max Pooling
      - ReLU
      - Residual Connection
      - Softmax
      Tasks:
      - Image Classification
      Training Data:
      - ImageNet
      ID: xception65
      Crop Pct: '0.903'
      Image Size: '299'
      Interpolation: bicubic
    Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/xception_aligned.py#L200
    Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_65-c9ae96e8.pth
    Results:
    - Task: Image Classification
      Dataset: ImageNet
      Metrics:
        Top 1 Accuracy: 79.55%
        Top 5 Accuracy: 94.66%
  - Name: xception71
    In Collection: Xception
    Metadata:
      FLOPs: 22817346560
      Parameters: 42340000
      File Size: 170295556
      Architecture:
      - 1x1 Convolution
      - Convolution
      - Dense Connections
      - Depthwise Separable Convolution
      - Global Average Pooling
      - Max Pooling
      - ReLU
      - Residual Connection
      - Softmax
      Tasks:
      - Image Classification
      Training Data:
      - ImageNet
      ID: xception71
      Crop Pct: '0.903'
      Image Size: '299'
      Interpolation: bicubic
    Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/xception_aligned.py#L219
    Weights: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_71-8eec7df1.pth
    Results:
    - Task: Image Classification
      Dataset: ImageNet
      Metrics:
        Top 1 Accuracy: 79.88%
        Top 5 Accuracy: 94.93%
  -->
  