| /external/tensorflow/tensorflow/compiler/xla/python/ |
| numpy_bridge.h | 43 PrimitiveType NumpyTypeToPrimitiveType(int np_type);
47 bool NumpyTypeIsValid(int np_type);
90 Status CopyNumpyArrayToLiteral(int np_type, PyArrayObject* py_array,
93 void CopyLiteralToNumpyArray(int np_type, const Literal& literal,
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| numpy_bridge.cc | 59 PrimitiveType NumpyTypeToPrimitiveType(int np_type) {
60 switch (np_type) {
88 LOG(FATAL) << "No XLA primitive type for Numpy type " << np_type;
92 bool NumpyTypeIsValid(int np_type) {
93 switch (np_type) {
205 PyObject* np_type; local
206 TF_ASSIGN_OR_RETURN(np_type, get_attr("np_dtype"));
207 if (np_type->ob_type != &PyArrayDescr_Type) {
210 if (!NumpyTypeIsValid(NumpyTypenum(np_type))) {
214 NumpyTypeToPrimitiveType(NumpyTypenum(np_type));
365 int np_type = PrimitiveTypeToNumpyType(literal.shape().element_type()); local
392 int np_type = PyArray_TYPE(py_array); local
[all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| matrix_exponential_op_test.py | 48 def _verifyExponential(self, x, np_type):
49 inp = x.astype(np_type)
53 np_ans = np.empty(x.shape, dtype=np_type)
56 np_ans = np.zeros(inp.shape, dtype=np_type)
65 for np_type in [np.float32, np.float64]:
66 self._verifyExponential(x, np_type)
69 for np_type in [np.complex64, np.complex128]:
70 self._verifyExponential(x, np_type)
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| matrix_solve_op_test.py | 38 for np_type in [np.float32, np.float64, np.complex64, np.complex128]:
39 if np_type == np.float32 or np_type == np.complex64:
44 if np_type is [np.float32, np.float64]:
45 a = x.real().astype(np_type)
46 b = y.real().astype(np_type)
48 a = x.astype(np_type)
49 b = y.astype(np_type)
59 a_ph = array_ops.placeholder(dtypes.as_dtype(np_type))
60 b_ph = array_ops.placeholder(dtypes.as_dtype(np_type))
[all...] |
| matrix_inverse_op_test.py | 36 def _verifyInverse(self, x, np_type):
38 y = x.astype(np_type)
53 for np_type in [np.float32, np.float64]:
54 self._verifyInverse(x, np_type)
57 for np_type in [np.complex64, np.complex128]:
58 self._verifyInverse(x, np_type)
|
| matrix_logarithm_op_test.py | 38 def _verifyLogarithm(self, x, np_type):
39 inp = x.astype(np_type)
48 for np_type in [np.complex64, np.complex128]:
49 self._verifyLogarithm(x, np_type)
|
| matrix_triangular_solve_op_test.py | 58 for np_type in dtypes:
59 a = x.astype(np_type)
60 b = y.astype(np_type)
|
| linalg_ops_test.py | 54 for np_type, atol in [(np.float32, 0.05), (np.float64, 1e-5)]:
59 _RandomPDMatrix(n, self.rng)]).astype(np_type)
62 rhs = self.rng.randn(2, n, k).astype(np_type)
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| embedding_ops_test.py | 154 np_type = "f" if dtype == dtypes.float32 else "d"
155 val = (np.random.rand(*shard_shape).astype(np_type)) + 1
[all...] |
| /external/tensorflow/tensorflow/python/lib/core/ |
| py_func.cc | 307 const int np_type = PyArray_TYPE(input); local
308 switch (np_type) {
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| embedding_ops_test.py | 593 np_type = "f" if dtype == dtypes.float32 else "d"
594 val = (np.random.rand(*shard_shape).astype(np_type)) + 1
|
