2023-04-09 19:21:45 +00:00
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# The type of float to use throughout a session.
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_FLOATX = "float32"
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# Epsilon fuzz factor used throughout the codebase.
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_EPSILON = 1e-7
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# Default image data format, one of "channels_last", "channels_first".
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_IMAGE_DATA_FORMAT = "channels_last"
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def epsilon():
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"""Return the value of the fuzz factor used in numeric expressions.
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Returns:
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A float.
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Example:
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>>> keras_core.backend.epsilon()
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1e-07
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"""
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return _EPSILON
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def set_epsilon(value):
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"""Set the value of the fuzz factor used in numeric expressions.
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Args:
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value: float. New value of epsilon.
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Example:
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>>> keras_core.backend.epsilon()
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1e-07
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>>> keras_core.backend.set_epsilon(1e-5)
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>>> keras_core.backend.epsilon()
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1e-05
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>>> keras_core.backend.set_epsilon(1e-7)
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"""
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global _EPSILON
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_EPSILON = value
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def floatx():
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"""Return the default float type, as a string.
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E.g. `'float16'`, `'float32'`, `'float64'`.
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Returns:
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String, the current default float type.
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Example:
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>>> keras_core.backend.floatx()
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'float32'
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"""
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return _FLOATX
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def set_floatx(value):
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"""Set the default float type.
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Note: It is not recommended to set this to float16 for training, as this
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will likely cause numeric stability issues. Instead, mixed precision, which
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is using a mix of float16 and float32, can be used by calling
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`keras_core.mixed_precision.set_global_policy('mixed_float16')`. See the
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[mixed precision guide](
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https://www.tensorflow.org/guide/keras/mixed_precision) for details.
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Args:
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value: String; `'float16'`, `'float32'`, or `'float64'`.
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Example:
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>>> keras_core.backend.floatx()
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'float32'
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>>> keras_core.backend.set_floatx('float64')
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>>> keras_core.backend.floatx()
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'float64'
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>>> keras_core.backend.set_floatx('float32')
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Raises:
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ValueError: In case of invalid value.
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"""
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global _FLOATX
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accepted_dtypes = {"float16", "float32", "float64"}
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if value not in accepted_dtypes:
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raise ValueError(
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2023-04-12 18:00:14 +00:00
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f"Unknown `floatx` value: {value}. "
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f"Expected one of {accepted_dtypes}"
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)
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_FLOATX = str(value)
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def image_data_format():
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"""Return the default image data format convention.
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Returns:
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A string, either `'channels_first'` or `'channels_last'`
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Example:
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>>> keras_core.backend.image_data_format()
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'channels_last'
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"""
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return _IMAGE_DATA_FORMAT
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def set_image_data_format(data_format):
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"""Set the value of the image data format convention.
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Args:
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data_format: string. `'channels_first'` or `'channels_last'`.
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Example:
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>>> keras_core.backend.image_data_format()
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'channels_last'
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>>> keras_core.backend.set_image_data_format('channels_first')
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>>> keras_core.backend.image_data_format()
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'channels_first'
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>>> keras_core.backend.set_image_data_format('channels_last')
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Raises:
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ValueError: In case of invalid `data_format` value.
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"""
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global _IMAGE_DATA_FORMAT
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accepted_formats = {"channels_last", "channels_first"}
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if data_format not in accepted_formats:
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raise ValueError(
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f"Unknown `data_format`: {data_format}. "
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f"Expected one of {accepted_formats}"
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)
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_IMAGE_DATA_FORMAT = str(data_format)
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