| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_Cumprod.pbtxt | 21 If `True`, perform exclusive cumprod.
32 By default, this op performs an inclusive cumprod, which means that the first
36 tf.cumprod([a, b, c]) # => [a, a * b, a * b * c]
39 By setting the `exclusive` kwarg to `True`, an exclusive cumprod is
43 tf.cumprod([a, b, c], exclusive=True) # => [1, a, a * b]
46 By setting the `reverse` kwarg to `True`, the cumprod is performed in the
50 tf.cumprod([a, b, c], reverse=True) # => [a * b * c, b * c, c]
58 tf.cumprod([a, b, c], exclusive=True, reverse=True) # => [b * c, c, 1]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | scan_ops_test.py | 60 elif func == np.cumprod:
160 np_out = handle_options(np.cumprod, x, axis, exclusive, reverse)
163 prod = math_ops.cumprod(p, axis, exclusive, reverse)
186 math_ops.cumprod(x, axis).eval(feed_dict={p: x})
220 math_ops.cumprod(input_tensor, -3).eval()
224 math_ops.cumprod(input_tensor, 2).eval()
228 math_ops.cumprod(input_tensor, [0]).eval()
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | scan_ops_test.py | 60 elif func == np.cumprod:
214 np_out = handle_options(np.cumprod, x, axis, exclusive, reverse)
216 tf_out = math_ops.cumprod(x, axis, exclusive, reverse).eval()
239 tf_out = math_ops.cumprod(x, axis).eval()
285 math_ops.cumprod(input_tensor, -3).eval()
289 math_ops.cumprod(input_tensor, 2).eval()
293 math_ops.cumprod(input_tensor, [0]).eval()
299 result = math_ops.cumprod(t, axis, exclusive, reverse)
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| /external/eigen/unsupported/test/ |
| D | cxx11_tensor_scan.cpp | 39 result = tensor.cumprod(0, Exclusive); in test_1d_scan()
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_conversion_ops.py | 135 leading_ones = math_ops.cumprod(dim_is_one)
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| D | ragged_gather_ops.py | 166 shape_cumprod = math_ops.cumprod(indices_shape)
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| D | ragged_array_ops.py | 198 split_size = math_ops.cumprod(mask_shape) + 1
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| D | ragged_tensor.py | 1605 dim_size = np.cumprod(input_shape)
1608 dim_size = math_ops.cumprod(input_shape)
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| /external/tensorflow/tensorflow/python/ops/numpy_ops/ |
| D | np_array_ops.py | 435 def cumprod(a, axis=None, dtype=None): # pylint: disable=missing-docstring function
447 return math_ops.cumprod(a, axis)
1760 index_scaling = math_ops.cumprod(
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| D | np_array_ops_test.py | 648 np_array_ops.cumprod(arg, *args, **kwargs),
649 np.cumprod(arg, *args, **kwargs))
|
| /external/tensorflow/tensorflow/python/ops/ |
| D | math_grad.py | 309 left = math_ops.cumprod(reshaped, axis=0, exclusive=True)
310 right = math_ops.cumprod(reshaped, axis=0, exclusive=True, reverse=True)
1990 prod = math_ops.cumprod(x, axis, exclusive=exclusive, reverse=reverse)
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| D | math_ops.py | 3969 def cumprod(x, axis=0, exclusive=False, reverse=False, name=None): function
4016 return gen_math_ops.cumprod(
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| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | math_test.py | 439 return math_ops.cumprod(
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| D | pfor.py | 2635 @RegisterPForWithArgs("Cumprod", math_ops.cumprod)
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.math.pbtxt | 112 name: "cumprod"
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| D | tensorflow.keras.backend.pbtxt | 124 name: "cumprod"
|
| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.math.pbtxt | 112 name: "cumprod"
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| D | tensorflow.keras.backend.pbtxt | 128 name: "cumprod"
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| D | tensorflow.pbtxt | 1072 name: "cumprod"
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| /external/tensorflow/tensorflow/python/ops/structured/ |
| D | structured_tensor.py | 1285 shape_cumprod = math_ops.cumprod(shape[:rank])
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| /external/tensorflow/third_party/py/numpy/tf_numpy_api/ |
| D | tensorflow.experimental.numpy.pbtxt | 312 name: "cumprod"
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| /external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
| D | TensorBase.h | 512 cumprod(const Index& axis, bool exclusive = false) const {
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| D | README.md | 1204 ### <Operation> cumprod(const Index& axis)
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | backend.py | 2376 def cumprod(x, axis=0): function
2386 return math_ops.cumprod(x, axis=axis)
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| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/ir/ |
| D | tf_generated_ops.td | 2519 By default, this op performs an inclusive cumprod, which means that the first
2523 tf.cumprod([a, b, c]) # => [a, a * b, a * b * c]
2526 By setting the `exclusive` kwarg to `True`, an exclusive cumprod is
2530 tf.cumprod([a, b, c], exclusive=True) # => [1, a, a * b]
2533 By setting the `reverse` kwarg to `True`, the cumprod is performed in the
2537 tf.cumprod([a, b, c], reverse=True) # => [a * b * c, b * c, c]
2545 tf.cumprod([a, b, c], exclusive=True, reverse=True) # => [b * c, c, 1]
|