tf.experimental.numpy.experimental_enable_numpy_behavior
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Enable NumPy behavior on Tensors.
tf.experimental.numpy.experimental_enable_numpy_behavior(
prefer_float32=False, dtype_conversion_mode='legacy'
)
Used in the notebooks
Enabling NumPy behavior has three effects:
- It adds to
tf.Tensor
some common NumPy methods such as T
,
reshape
and ravel
.
- It changes dtype promotion in
tf.Tensor
operators to be
compatible with NumPy. For example,
tf.ones([], tf.int32) + tf.ones([], tf.float32)
used to throw a
"dtype incompatible" error, but after this it will return a
float64 tensor (obeying NumPy's promotion rules).
- It enhances
tf.Tensor
's indexing capability to be on par with
NumPy's.
Args |
prefer_float32
|
Controls whether dtype inference will use float32 for Python
floats, or float64 (the default and the NumPy-compatible behavior).
|
dtype_conversion_mode
|
a string that specifies promotion mode. This string
corresponds to a PromoMode Enum and can be 'off', 'legacy', 'safe', or
'all'. 'safe' or 'all' mode enables the auto dtype conversion semantics.
|
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Last updated 2024-04-26 UTC.
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