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remove t.viz() functionality and show deprecation warning instead
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,117 @@ | ||
| from __future__ import annotations | ||
| import warnings | ||
| import numpy as np | ||
|
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| def tensor_to_numpy(tensor, **kwargs) -> np.ndarray: | ||
| """ | ||
| Converts a tensor of unknown type to a numpy array. | ||
| Args: | ||
| tensor: The tensor to be converted. | ||
| Returns: | ||
| The converted numpy array. | ||
| """ | ||
| mro_strings = mro_to_strings(tensor.__class__.__mro__) | ||
|
|
||
| if "numpy.ndarray" in mro_strings: | ||
| return tensor | ||
| elif "torch.Tensor" in mro_strings: | ||
| return _tensor_to_numpy_torch(tensor, **kwargs) | ||
| elif "tensorflow.python.types.core.Tensor" in mro_strings: | ||
| return _tensor_to_numpy_tensorflow(tensor, **kwargs) | ||
| elif "jaxlib.xla_extension.DeviceArray" in mro_strings: | ||
| return _tensor_to_numpy_jax(tensor, **kwargs) | ||
| elif "PIL.Image.Image" in mro_strings: | ||
| return _tensor_to_numpy_pillow(tensor, **kwargs) | ||
| else: | ||
| raise NotImplementedError( | ||
| f"Conversion of tensor of type {type(tensor)} is not supported. Please raise an issue of you think this is a bug or should be implemented." | ||
| ) | ||
|
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|
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| def mro_to_strings(mro) -> list[str]: | ||
| """ | ||
| Converts the __mro__ of a class to a list of module.class_name strings. | ||
| Args: | ||
| mro: The __mro__ to be converted. | ||
| Returns: | ||
| The converted list of strings. | ||
| """ | ||
| return [f"{c.__module__}.{c.__name__}" for c in mro] | ||
|
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| def _tensor_to_numpy_torch(tensor) -> np.ndarray: | ||
| if tensor.__class__.__name__ == "MaskedTensor": # hacky - but we shouldn't import torch here | ||
| return np.ma.masked_array(tensor.get_data(), ~tensor.get_mask()) | ||
| try: # pylint: disable=duplicate-code | ||
| return tensor.numpy() | ||
| except RuntimeError as e: | ||
| raise NotImplementedError( | ||
| f"{e}: It looks like tensors of type {type(tensor)} cannot be converted to numpy arrays out-of-the-box. Raise an issue if you need to visualize them." | ||
| ) from e | ||
| except Exception as e: | ||
| raise RuntimeError( | ||
| f"An unexpected error occurred while converting tensor of type {type(tensor)} to numpy array: {e}" | ||
| ) from e | ||
|
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| def _tensor_to_numpy_tensorflow(tensor) -> np.ndarray: | ||
| if tensor.__class__.__name__ == "RaggedTensor": # hacky - but we shouldn't import torch here | ||
| warnings.warn( | ||
| "Tensorflow RaggedTensors are currently converted to dense tensors by filling with the value 0. Values that are actually 0 and filled-in values will appear indistinguishable. This behavior will change in the future." | ||
| ) | ||
| return _tensor_to_numpy_tensorflow(tensor.to_tensor()) | ||
| if tensor.__class__.__name__ == "SparseTensor": | ||
| raise ValueError("Tensorflow SparseTensors are not yet supported by TensorHue.") | ||
| try: # pylint: disable=duplicate-code | ||
| return tensor.numpy() | ||
| except RuntimeError as e: | ||
| raise NotImplementedError( | ||
| f"{e}: It looks like tensors of type {type(tensor)} cannot be converted to numpy arrays out-of-the-box. Raise an issue if you need to visualize them." | ||
| ) from e | ||
| except Exception as e: | ||
| raise RuntimeError( | ||
| f"An unexpected error occurred while converting tensor of type {type(tensor)} to numpy array: {e}" | ||
| ) from e | ||
|
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| def _tensor_to_numpy_jax(tensor) -> np.ndarray: | ||
| not_implemented = {"ShapedArray", "UnshapedArray", "AbstractArray"} | ||
| if {c.__name__ for c in tensor.__class__.__mro__}.intersection( | ||
| not_implemented | ||
| ): # hacky - but we shouldn't import jax here | ||
| raise NotImplementedError( | ||
| f"Jax arrays of type {tensor.__class__.__name__} cannot be visualized. Raise an issue if you believe this is wrong." | ||
| ) | ||
| try: | ||
| array = np.asarray(tensor) | ||
| if array.dtype == "object": | ||
| raise RuntimeError("Got non-visualizable dtype 'object'.") | ||
| return array | ||
| except RuntimeError as e: | ||
| raise NotImplementedError( | ||
| f"{e}: It looks like JAX arrays of type {type(tensor)} cannot be converted to numpy arrays out-of-the-box. Raise an issue if you need to visualize them." | ||
| ) from e | ||
| except Exception as e: | ||
| raise RuntimeError( | ||
| f"An unexpected error occurred while converting tensor of type {type(tensor)} to numpy array: {e}" | ||
| ) from e | ||
|
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| def _tensor_to_numpy_pillow(image, thumbnail, max_size) -> np.ndarray: | ||
| try: | ||
| image = image.convert("RGB") | ||
| except Exception as e: | ||
| raise ValueError("Could not convert image from mode '{mode}' to 'RGB'.") from e | ||
|
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| if thumbnail: | ||
| image.thumbnail(max_size) | ||
|
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| array = np.array(image) | ||
| assert array.dtype == "uint8" | ||
|
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| return array |
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