Python LazyLoader示例

示例#1

文件： linear_operator_full_matrix.py 项目： vishalbelsare/probability

    def _matmul(self, x, adjoint=False, adjoint_arg=False):
        return _linalg.matmul(self._matrix,
                              x,
                              adjoint_a=adjoint,
                              adjoint_b=adjoint_arg)

    def _solve(self, rhs, adjoint=False, adjoint_arg=False):
        return self._dense_solve(rhs, adjoint=adjoint, adjoint_arg=adjoint_arg)

    def _to_dense(self):
        return self._matrix

    @property
    def _composite_tensor_fields(self):
        return ("matrix", )


import numpy as np
from tensorflow_probability.python.internal.backend.numpy import linalg_impl as _linalg
from tensorflow_probability.python.internal.backend.numpy import ops as _ops
from tensorflow_probability.python.internal.backend.numpy.gen import tensor_shape

from tensorflow_probability.python.internal.backend.numpy import private
distribution_util = private.LazyLoader(
    "distribution_util", globals(),
    "tensorflow_probability.substrates.numpy.internal.distribution_util")
tensorshape_util = private.LazyLoader(
    "tensorshape_util", globals(),
    "tensorflow_probability.substrates.numpy.internal.tensorshape_util")

示例#2

文件： linear_operator_identity.py 项目： wataruhashimoto52/probability

            return _linalg.set_diag(mat, new_diag)

    def _eigvals(self):
        return self._ones_diag() * self.multiplier[..., _ops.newaxis]

    def _cond(self):
        # Condition number for a scalar time identity matrix is one, except when the
        # scalar is zero.
        return array_ops.where_v2(math_ops.equal(self._multiplier, 0.),
                                  _ops.cast(np.nan, dtype=self.dtype),
                                  _ops.cast(1., dtype=self.dtype))

    @property
    def multiplier(self):
        """The [batch] scalar `Tensor`, `c` in `cI`."""
        return self._multiplier


import numpy as np
from tensorflow_probability.python.internal.backend.numpy import linalg_impl as _linalg
from tensorflow_probability.python.internal.backend.numpy import ops as _ops
from tensorflow_probability.python.internal.backend.numpy.gen import tensor_shape

from tensorflow_probability.python.internal.backend.numpy import private
distribution_util = private.LazyLoader(
    "distribution_util", globals(),
    "tensorflow_probability.python.internal._numpy.distribution_util")
tensorshape_util = private.LazyLoader(
    "tensorshape_util", globals(),
    "tensorflow_probability.python.internal._numpy.tensorshape_util")