Add label_shapes parameter to KerasEstimator and TorchEstimator #2140
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abditag2
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tgaddair
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Jul 25, 2020
horovod/spark/common/util.py
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| col_size = metadata[col]['shape'] | ||
| if col_size is None: | ||
| def _check_label_cols_size(target_shapes): | ||
| for _idx, _col, target_shape in zip(range(label_count), label_columns, target_shapes): |
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No need to use _ here, that's only for private methods / variables.
horovod/spark/common/util.py
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| .format(col=_col, label=_col_size, idx=_idx, output=target_size)) | ||
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| if output_shapes is not None: | ||
| _check_label_cols_size(output_shapes) |
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Seems this should only be done if label_shapes is None, right? Otherwise, we will be forcing the model output size to equal the label size, which may not be correct (for these custom loss functions).
horovod/spark/torch/remote.py
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| labels = [label.reshape(output.shape) | ||
| if output.shape.numel() == label.shape.numel() else label | ||
| for label, output in zip(labels, outputs)] | ||
| # If label_shapes parameter is not provided, reshape the label columns |
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Can move this comment into the else branch so it's closer to the code it's describing.
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Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
Signed-off-by: Fardin Abdi <fardin@uber.com>
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Description
Fixes # (issue).
Review process to land