| /external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
| D | not_supported.txt | 157 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True
158 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False
159 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True
160 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False
161 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True
162 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False
163 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True
164 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False
165 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=True
166 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=False
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| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_boolean_mask_op_test.py | 51 keepdims=False,
57 keepdims=True,
63 keepdims=False,
69 keepdims=True,
75 keepdims=False,
84 keepdims=True,
90 keepdims=True,
96 keepdims=True,
103 keepdims=True,
109 keepdims=False,
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| D | ragged_math_ops.py | 403 keepdims, argument
443 if keepdims:
470 rt_input, axis[-1], keepdims)
472 inner_reduced, axis[:-1], keepdims)
498 rt_input.values, axis - 1, keepdims))
501 def reduce_sum(input_tensor, axis=None, keepdims=None, name=None): argument
505 axis, keepdims, name or 'RaggedReduceSum')
508 def reduce_prod(input_tensor, axis=None, keepdims=None, name=None): argument
512 axis, keepdims, name or 'RaggedReduceProd')
515 def reduce_min(input_tensor, axis=None, keepdims=None, name=None): argument
[all …]
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| D | ragged_array_ops.py | 37 def boolean_mask(data, mask, keepdims=False, name=None): argument
162 masked_values = boolean_mask(data, mask, keepdims)
165 if keepdims:
187 masked_values = boolean_mask(data.values, segment_mask, keepdims=False)
197 return boolean_mask(data, mask, keepdims)
204 if mask.shape.ndims >= 2 and keepdims:
215 if mask.shape.ndims > 2 and keepdims:
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| /external/tensorflow/tensorflow/python/ops/ |
| D | math_ops.py | 1304 def _may_reduce_to_scalar(keepdims, axis, output): argument
1306 if not common_shapes.has_fully_defined_shape(output) and (not keepdims) and (
1317 keepdims=None, argument
1362 keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims,
1364 return reduce_sum(input_tensor, axis, keepdims, name)
1369 def reduce_sum(input_tensor, axis=None, keepdims=False, name=None): argument
1407 keepdims = False if keepdims is None else keepdims
1409 keepdims, axis,
1411 input_tensor, _ReductionDims(input_tensor, axis), keepdims,
1416 def reduce_euclidean_norm(input_tensor, axis=None, keepdims=False, name=None): argument
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| D | linalg_ops.py | 430 keepdims=None, argument
492 keepdims=keepdims,
503 keepdims=None, argument
564 keepdims = deprecation.deprecated_argument_lookup('keepdims', keepdims,
566 if keepdims is None:
567 keepdims = False
615 keepdims=True),
621 tensor * math_ops.conj(tensor), axis, keepdims=True))
628 result = math_ops.reduce_sum(result, sum_axis, keepdims=True)
630 result = math_ops.reduce_max(result, axis[-1], keepdims=True)
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| D | sparse_ops.py | 1022 sp_input, axis=None, keepdims=None, output_is_sparse=False, name=None): argument
1078 if keepdims is None:
1079 keepdims = False
1088 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
1095 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
1106 def sparse_reduce_max(sp_input, axis=None, keepdims=None, argument
1160 keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims,
1162 if keepdims is None:
1163 keepdims = False
1167 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims)
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| D | nn_impl.py | 435 square_sum = math_ops.reduce_sum(math_ops.square(x), axis, keepdims=True)
812 keepdims=None): argument
839 "keepdims", keepdims, "keep_dims", keep_dims)
861 m_ss = math_ops.reduce_sum(m_ss, axes, keepdims=keep_dims, name="mean_ss")
862 v_ss = math_ops.reduce_sum(v_ss, axes, keepdims=keep_dims, name="var_ss")
867 def sufficient_statistics_v2(x, axes, shift=None, keepdims=False, name=None): argument
892 x=x, axes=axes, shift=shift, keep_dims=keepdims, name=name)
934 keepdims=None): argument
963 "keepdims", keepdims, "keep_dims", keep_dims)
972 mean = math_ops.reduce_mean(y, axes, keepdims=True, name="mean")
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| D | nn_grad.py | 295 sum_channels = math_ops.reduce_sum(grad_softmax * softmax, -1, keepdims=True)
314 return grad - math_ops.reduce_sum(grad, -1, keepdims=True) * softmax
943 keepdims = False
946 keepdims = True
950 mean_grad_y = math_ops.reduce_mean(grad_y, reduce_axis, keepdims=keepdims)
951 mean_x = math_ops.reduce_mean(x, reduce_axis, keepdims=keepdims)
955 keepdims=keepdims)
959 grad_y * x_offset, axis=reduce_axis, keepdims=keepdims)
963 grad_y * x_offset, axis=reduce_axis, keepdims=keepdims)
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| D | string_ops.py | 334 keepdims=None): argument
336 "keepdims", keepdims, "keep_dims", keep_dims)
352 keepdims=False, argument
356 inputs, axis, keep_dims=keepdims, separator=separator, name=name)
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | reduction_ops_test.py | 120 def _tf_reduce(self, x, reduction_axes, keepdims): argument
123 def _np_reduce(self, x, reduction_axes, keepdims): argument
138 def _compare(self, x, reduction_axes, keepdims, feed_dict=None): argument
139 np_ans = self._np_reduce(x, reduction_axes, keepdims)
141 tf_ans = self._tf_reduce(x, reduction_axes, keepdims)
150 self._compare(x, reduction_axes, keepdims=False, feed_dict=feed_dict)
151 self._compare(x, reduction_axes, keepdims=True, feed_dict=feed_dict)
181 def _tf_reduce(self, x, reduction_axes, keepdims): argument
182 return math_ops.reduce_sum(x, reduction_axes, keepdims)
184 def _np_reduce(self, x, reduction_axes, keepdims): argument
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| D | reduction_ops_test_big.py | 32 def _tf_reduce(self, x, reduction_axes, keepdims): argument
39 def _tf_reduce_max(self, x, reduction_axes, keepdims): argument
40 return math_ops.reduce_max(x, reduction_axes, keepdims)
42 def _tf_reduce_all(self, x, reduction_axes, keepdims): argument
43 return math_ops.reduce_all(x, reduction_axes, keepdims)
45 def _tf_reduce_mean(self, x, reduction_axes, keepdims): argument
46 return math_ops.reduce_mean(x, reduction_axes, keepdims)
48 def _tf_reduce_sum(self, x, reduction_axes, keepdims): argument
49 return math_ops.reduce_sum(x, reduction_axes, keepdims)
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| D | norm_op_test.py | 70 np_norm = np.linalg.norm(matrix, ord=ord_, axis=axis_, keepdims=keep_dims_)
75 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_)
80 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_)
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| /external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
| D | metric_loss_ops.py | 53 math_ops.reduce_sum(math_ops.square(feature), axis=[1], keepdims=True),
57 keepdims=True)) - 2.0 * math_ops.matmul(feature,
134 axis_minimums = math_ops.reduce_min(data, dim, keepdims=True)
137 keepdims=True) + axis_minimums
153 axis_maximums = math_ops.reduce_max(data, dim, keepdims=True)
156 keepdims=True) + axis_maximums
204 math_ops.cast(mask, dtype=dtypes.float32), 1, keepdims=True),
291 labels_remapped /= math_ops.reduce_sum(labels_remapped, 1, keepdims=True)
397 labels_remapped /= math_ops.reduce_sum(labels_remapped, 1, keepdims=True)
450 row_minimums = math_ops.reduce_min(diff, 1, keepdims=True)
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| D | batch_normalization_test.py | 112 keepdims = len(event_dims) > 1
115 x_, axis=reduction_axes, keepdims=keepdims)
116 expected_batch_var = np.var(x_, axis=reduction_axes, keepdims=keepdims)
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.math.pbtxt | 105 …argspec: "args=[\'input\', \'axis\', \'keepdims\', \'dtype\', \'name\'], varargs=None, keywords=No…
305 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
309 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
313 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
317 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
321 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
325 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
329 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
333 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
337 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.math.pbtxt | 105 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'dtype\', \'name\', \'reduction_indices…
305 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
309 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
313 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
317 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
321 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
325 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
329 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
333 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_…
337 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, …
[all …]
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| D | tensorflow.sparse.pbtxt | 65 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
69 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
73 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
77 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
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| /external/tensorflow/tensorflow/python/keras/ |
| D | constraints.py | 70 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
112 math_ops.square(w), axis=self.axis, keepdims=True)))
156 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
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| D | activations.py | 61 e = math_ops.exp(x - math_ops.reduce_max(x, axis=axis, keepdims=True))
62 s = math_ops.reduce_sum(e, axis=axis, keepdims=True)
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| D | kmeans_test.py | 49 return x / np.sqrt(np.sum(x * x, axis=-1, keepdims=True))
221 keepdims=True) - 2 * np.dot(points, np.transpose(clusters)) +
222 np.transpose(np.sum(np.square(clusters), axis=1, keepdims=True)))
326 np.mean(normalize(self.points)[0:4, :], axis=0, keepdims=True))[
329 np.mean(normalize(self.points)[4:, :], axis=0, keepdims=True))[
393 np.mean(normalize(points)[0:2, :], axis=0, keepdims=True))[0],
395 np.mean(normalize(points)[2:4, :], axis=0, keepdims=True))[0],
397 np.mean(normalize(points)[4:, :], axis=0, keepdims=True))[0]
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | gmm_ops.py | 57 x -= math_ops.reduce_mean(x, 0, keepdims=True)
60 math_ops.square(x), 0, keepdims=True) / (num_points - 1)
317 math_ops.log(self._covs + 1e-3), 1, keepdims=True)
355 self._probs[shard_id], axis=1, keepdims=True)
379 self._w[shard_id], 0, keepdims=True)
459 math_ops.reduce_logsumexp(op, axis=2, keepdims=True), axis=0)
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| D | kmeans_test.py | 49 return x / np.sqrt(np.sum(x * x, axis=-1, keepdims=True))
214 np.sum(np.square(points), axis=1, keepdims=True) -
216 np.sum(np.square(clusters), axis=1, keepdims=True)))
359 keepdims=True))[0],
362 keepdims=True))[0]
426 np.mean(normalize(points)[0:2, :], axis=0, keepdims=True))[0],
428 np.mean(normalize(points)[2:4, :], axis=0, keepdims=True))[0],
430 keepdims=True))[0]
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| /external/tensorflow/tensorflow/contrib/image/python/kernel_tests/ |
| D | interpolate_spline_test.py | 112 keepdims=True)
119 keepdims=True)
145 keepdims=True)
152 keepdims=True)
|
| /external/tensorflow/tensorflow/python/layers/ |
| D | normalization_test.py | 1114 means = np.mean(sub_batched, axis=0, keepdims=True)
1115 variances = np.var(sub_batched, axis=0, keepdims=True)
1117 avg_means = np.mean(means, axis=1, keepdims=True)
1118 avg_variances = np.mean(variances, axis=1, keepdims=True)
1167 means = np.mean(sub_batched, axis=(0, 2, 3), keepdims=True)
1168 variances = np.var(sub_batched, axis=(0, 2, 3), keepdims=True)
1170 avg_means = np.mean(means, axis=1, keepdims=True)
1171 avg_variances = np.mean(variances, axis=1, keepdims=True)
1221 means = np.mean(sub_batched, axis=(0, 3, 4), keepdims=True)
1222 variances = np.var(sub_batched, axis=(0, 3, 4), keepdims=True)
[all …]
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