eabdb87f9f
* Add numpy ops (initial batch) and some config * Add unit test * fix call * Revert "fix call" This reverts commit 6748ad183029ff4b97317b77ceed8661916bb9a0. * full unit test coverage * fix setup.py
105 lines
3.2 KiB
Python
105 lines
3.2 KiB
Python
import json
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import os
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import sys
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from keras_core.backend.common import StatelessScope
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from keras_core.backend.common import standardize_dtype
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from keras_core.backend.common import standardize_shape
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from keras_core.backend.config import epsilon
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from keras_core.backend.config import floatx
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from keras_core.backend.config import image_data_format
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from keras_core.backend.config import set_epsilon
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from keras_core.backend.config import set_floatx
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from keras_core.backend.config import set_image_data_format
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from keras_core.backend.keras_tensor import KerasTensor
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from keras_core.backend.keras_tensor import any_symbolic_tensors
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from keras_core.backend.keras_tensor import is_keras_tensor
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from keras_core.utils.io_utils import print_msg
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# Set Keras base dir path given KERAS_HOME env variable, if applicable.
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# Otherwise either ~/.keras or /tmp.
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if "KERAS_HOME" in os.environ:
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_keras_dir = os.environ.get("KERAS_HOME")
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else:
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_keras_base_dir = os.path.expanduser("~")
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if not os.access(_keras_base_dir, os.W_OK):
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_keras_base_dir = "/tmp"
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_keras_dir = os.path.join(_keras_base_dir, ".keras")
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# Default backend: TensorFlow.
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_BACKEND = "tensorflow"
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# Attempt to read Keras config file.
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_config_path = os.path.expanduser(os.path.join(_keras_dir, "keras.json"))
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if os.path.exists(_config_path):
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try:
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with open(_config_path) as f:
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_config = json.load(f)
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except ValueError:
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_config = {}
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_floatx = _config.get("floatx", floatx())
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assert _floatx in {"float16", "float32", "float64"}
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_epsilon = _config.get("epsilon", epsilon())
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assert isinstance(_epsilon, float)
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_backend = _config.get("backend", _BACKEND)
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_image_data_format = _config.get("image_data_format", image_data_format())
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assert _image_data_format in {"channels_last", "channels_first"}
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set_floatx(_floatx)
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set_epsilon(_epsilon)
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set_image_data_format(_image_data_format)
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_BACKEND = _backend
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# Save config file, if possible.
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if not os.path.exists(_keras_dir):
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try:
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os.makedirs(_keras_dir)
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except OSError:
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# Except permission denied and potential race conditions
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# in multi-threaded environments.
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pass
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if not os.path.exists(_config_path):
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_config = {
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"floatx": floatx(),
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"epsilon": epsilon(),
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"backend": _BACKEND,
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"image_data_format": image_data_format(),
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}
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try:
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with open(_config_path, "w") as f:
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f.write(json.dumps(_config, indent=4))
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except IOError:
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# Except permission denied.
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pass
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# Set backend based on KERAS_BACKEND flag, if applicable.
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if "KERAS_BACKEND" in os.environ:
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_backend = os.environ["KERAS_BACKEND"]
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if _backend:
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_BACKEND = _backend
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# Import backend functions.
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if _BACKEND == "tensorflow":
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print_msg("Using TensorFlow backend")
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from keras_core.backend.tensorflow import *
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elif _BACKEND == "jax":
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print_msg("Using JAX backend.")
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from keras_core.backend.jax import *
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else:
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raise ValueError(f"Unable to import backend : {_BACKEND}")
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def backend():
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"""Publicly accessible method for determining the current backend.
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Returns:
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String, the name of the backend Keras is currently using.
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Example:
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>>> keras.backend.backend()
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'tensorflow'
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"""
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return _BACKEND
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