| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_reduce_op_test.py | 55 ragged_reduce_op=ragged_math_ops.reduce_sum,
61 ragged_reduce_op=ragged_math_ops.reduce_sum,
67 ragged_reduce_op=ragged_math_ops.reduce_sum,
73 ragged_reduce_op=ragged_math_ops.reduce_sum,
153 ragged_reduce_op=ragged_math_ops.reduce_sum,
179 ragged_reduce_op=ragged_math_ops.reduce_sum,
208 ragged_reduce_op=ragged_math_ops.reduce_sum,
240 ragged_reduce_op=ragged_math_ops.reduce_sum,
245 ragged_reduce_op=ragged_math_ops.reduce_sum,
250 ragged_reduce_op=ragged_math_ops.reduce_sum,
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| D | ragged_map_fn_op_test.py | 59 fn=lambda x: array_ops.stack([mo.reduce_mean(x), mo.reduce_sum(x)]),
103 fn=lambda x: ragged_math_ops.reduce_sum(x, axis=1),
111 fn=lambda x: ragged_math_ops.reduce_sum(x, axis=0),
119 fn=ragged_math_ops.reduce_sum,
180 return mo.reduce_sum(f['batman']) + mo.reduce_sum(f['robin'])
262 fn = lambda x: ragged_math_ops.reduce_sum(x, axis=0)
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| D | ragged_math_ops.py | 546 def reduce_sum(input_tensor, axis=None, keepdims=None, name=None): function
550 reduce_op=math_ops.reduce_sum,
593 total = reduce_sum(input_tensor, axis, keepdims)
600 count = reduce_sum(ones, axis, keepdims)
626 reduce_sum(_cast(input_tensor, dtypes.int32), axis, keepdims),
638 _set_ragged_reduce_docstring(reduce_sum, 'sum', 'summed', '0',
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| /external/tensorflow/tensorflow/python/ops/ |
| D | math_grad.py | 233 math_ops.reduce_sum(indicators, op.inputs[1]), output_shape_kept_dims)
690 return (array_ops.reshape(math_ops.reduce_sum(partial_x * grad, rx), sx),
691 array_ops.reshape(math_ops.reduce_sum(partial_y * grad, ry), sy))
707 return (array_ops.reshape(math_ops.reduce_sum(partial_x * grad, rx), sx),
708 array_ops.reshape(math_ops.reduce_sum(partial_y * grad, ry), sy))
724 return (array_ops.reshape(math_ops.reduce_sum(partial_x * grad, rx), sx),
725 array_ops.reshape(math_ops.reduce_sum(partial_y * grad, ry), sy))
958 math_ops.reduce_sum(math_ops.mul_no_nan(partial_a, grad), ra), sa),
960 math_ops.reduce_sum(math_ops.mul_no_nan(partial_x, grad), rx),
963 return (array_ops.reshape(math_ops.reduce_sum(partial_a * grad, ra), sa),
[all …]
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| D | clip_ops.py | 148 gx = array_ops.reshape(math_ops.reduce_sum(xgrad, rx), sx)
149 gy = array_ops.reshape(math_ops.reduce_sum(ygrad, ry), sy)
150 gz = array_ops.reshape(math_ops.reduce_sum(zgrad, rz), sz)
198 l2sum = math_ops.reduce_sum(values * values, axes, keepdims=True)
256 half_squared_norm = math_ops.reduce_sum(array_ops.stack(half_squared_norms))
398 math_ops.reduce_sum(t * t, math_ops.range(array_ops.rank(t))))
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| D | linalg_grad.py | 363 math_ops.reduce_sum(grad_x, bx_start + rx), x_shape)
365 math_ops.reduce_sum(grad_y, by_start + ry), y_shape)
631 grad_a = array_ops.reshape(math_ops.reduce_sum(grad_a, axis=ra), a_shape)
632 grad_b = array_ops.reshape(math_ops.reduce_sum(grad_b, axis=rb), b_shape)
838 superdiag_grad = math_ops.reduce_sum(_LeftShift(rhs_conj) * grad, axis=-1)
839 maindiag_grad = math_ops.reduce_sum(rhs_conj * grad, axis=-1)
840 subdiag_grad = math_ops.reduce_sum(_RightShift(rhs_conj) * grad, axis=-1)
917 diag = math_ops.reduce_sum(x * y_tr, axis=-1)
922 superdiag = math_ops.reduce_sum(
924 subdiag = math_ops.reduce_sum(
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| D | metrics_impl.py | 376 num_values = math_ops.reduce_sum(weights)
378 update_total_op = state_ops.assign_add(total, math_ops.reduce_sum(values))
581 math_ops.reduce_sum(
593 math_ops.reduce_sum(
605 math_ops.reduce_sum(
617 math_ops.reduce_sum(
800 return math_ops.reduce_sum(
829 return math_ops.reduce_sum(
834 return math_ops.reduce_sum(
839 return math_ops.reduce_sum(
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| D | nccl_ops_test.py | 153 self._Test(partial(_NcclReduce, nccl_ops.reduce_sum), lambda x, y: x + y)
156 self._TestGradient(partial(_NcclReduce, nccl_ops.reduce_sum),
189 single_reduce_tensors = _NcclReduce(nccl_ops.reduce_sum, tensors, devices)
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | dirichlet.py | 201 self._total_concentration = math_ops.reduce_sum(self._concentration, -1)
240 return gamma_sample / math_ops.reduce_sum(gamma_sample, -1, keepdims=True)
252 return math_ops.reduce_sum(math_ops.xlogy(self.concentration - 1., x), -1)
263 - math_ops.reduce_sum(
333 math_ops.reduce_sum(x, -1),
406 math_ops.reduce_sum(d1.concentration, axis=-1, keepdims=True))
410 return (math_ops.reduce_sum(concentration_diff * digamma_diff, axis=-1) -
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| D | multinomial.py | 266 x = math_ops.reduce_sum(array_ops.one_hot(x, depth=k), axis=-2) # [n, k]
285 return math_ops.reduce_sum(counts * nn_ops.log_softmax(self.logits), -1)
314 self.total_count, math_ops.reduce_sum(counts, -1),
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| D | dirichlet_multinomial.py | 222 self._total_concentration = math_ops.reduce_sum(self._concentration, -1)
275 x = math_ops.reduce_sum(array_ops.one_hot(draws, depth=k), -2)
353 self.total_count, math_ops.reduce_sum(counts, -1),
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| /external/tensorflow/tensorflow/python/eager/ |
| D | tape_test.py | 39 r = math_ops.reduce_sum(mm)
90 return math_ops.reduce_sum(mm)
104 return math_ops.reduce_sum(mm)
118 return math_ops.reduce_sum(mm)
133 return r + math_ops.reduce_sum(mm)
142 tf_rr = 2 * math_ops.reduce_sum(tf_mm)
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | reduce_benchmark_test.py | 59 backprop.gradients_function(math_ops.reduce_sum, [0])(tensor)
68 backprop.gradients_function(math_ops.reduce_sum, [0])(tensor)
80 reduction = math_ops.reduce_sum(tensor)
97 reduction = math_ops.reduce_sum(tensor)
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | control_flow_test.py | 41 if math_ops.reduce_sum(inputs) > 0:
75 if math_ops.reduce_sum(inputs) > 0:
90 if math_ops.reduce_sum(inputs) > 0:
101 if math_ops.reduce_sum(inputs) > 0:
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| /external/tensorflow/tensorflow/python/ops/losses/ |
| D | losses_impl.py | 86 total_loss = math_ops.reduce_sum(losses)
124 return math_ops.reduce_sum(
129 return math_ops.reduce_sum(present, name=scope)
190 loss = math_ops.reduce_sum(weighted_losses)
193 loss, math_ops.reduce_sum(array_ops.ones_like(losses) * weights))
310 losses = 1 - math_ops.reduce_sum(radial_diffs, axis=(axis,), keepdims=True)
565 sum_squares_diff_per_batch = math_ops.reduce_sum(
574 sum_diff = math_ops.reduce_sum(diffs, axis=axis, keepdims=True)
583 loss = math_ops.reduce_sum(weighted_losses)
586 math_ops.reduce_sum(num_present_per_batch) > 0,
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| /external/tensorflow/tensorflow/python/grappler/ |
| D | layout_optimizer_test.py | 335 output = math_ops.reduce_sum(split[0])
401 reduce_sum = math_ops.reduce_sum(conv)
402 output = array_ops.identity(reduce_sum)
462 reduce_sum = math_ops.reduce_sum(conv, axis=[1, 2])
463 squeeze = array_ops.squeeze(reduce_sum)
493 reduce_sum = math_ops.reduce_sum(conv, axis=[1, 2], keepdims=True)
494 squeeze = array_ops.squeeze(reduce_sum, axis=[1, 2])
524 reduce_sum = math_ops.reduce_sum(conv, axis=[0, 1, 2], keepdims=True)
525 squeeze = array_ops.squeeze(reduce_sum, axis=[0, 1, 2])
555 reduce_sum = math_ops.reduce_sum(conv, axis=[1, 2, 3])
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| /external/tensorflow/tensorflow/python/keras/utils/ |
| D | kernelized_utils.py | 85 diff_squared_l2_norm = math_ops.reduce_sum(
115 diff_l1_norm = math_ops.reduce_sum(
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| D | losses_utils.py | 48 total_loss = math_ops.reduce_sum(losses)
64 loss = math_ops.reduce_sum(weighted_losses)
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| /external/tensorflow/tensorflow/python/layers/ |
| D | convolutional_test.py | 215 reg = lambda x: 0.1 * math_ops.reduce_sum(x)
227 reg = lambda x: 0.1 * math_ops.reduce_sum(x)
312 k_constraint = lambda x: x / math_ops.reduce_sum(x)
323 k_constraint = lambda x: x / math_ops.reduce_sum(x)
334 k_constraint = lambda x: x / math_ops.reduce_sum(x)
469 reg = lambda x: 0.1 * math_ops.reduce_sum(x)
481 reg = lambda x: 0.1 * math_ops.reduce_sum(x)
493 reg = lambda x: 0.1 * math_ops.reduce_sum(x)
512 d_constraint = lambda x: x / math_ops.reduce_sum(x)
513 p_constraint = lambda x: x / math_ops.reduce_sum(x)
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| /external/tensorflow/tensorflow/tools/compatibility/testdata/ |
| D | test_file_v0_11.py | 57 tf.reduce_sum(
60 tf.reduce_sum(
62 self.assertAllEqual(tf.reduce_sum(a, [0, 1]).eval(), 21.0)
221 tf.scalar_summary("scalar_reduce_var", tf.reduce_sum(var)),
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| /external/tensorflow/tensorflow/python/keras/ |
| D | regularizers.py | 219 regularization += self.l1 * math_ops.reduce_sum(math_ops.abs(x))
221 regularization += self.l2 * math_ops.reduce_sum(math_ops.square(x))
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| D | constraints.py | 73 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
114 math_ops.reduce_sum(
159 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
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| D | metrics.py | 334 values = math_ops.reduce_sum(
341 value_sum = math_ops.reduce_sum(values)
356 num_values = math_ops.reduce_sum(sample_weight)
2036 by_label_auc = math_ops.reduce_sum(
2044 math_ops.reduce_sum(
2046 math_ops.reduce_sum(self.label_weights),
2049 return math_ops.reduce_sum(pr_auc_increment, name='interpolate_pr_auc')
2085 by_label_auc = math_ops.reduce_sum(
2094 math_ops.reduce_sum(
2096 math_ops.reduce_sum(self.label_weights),
[all …]
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| /external/tensorflow/tensorflow/python/data/experimental/ops/ |
| D | resampling.py | 148 proportion_rejected = math_ops.reduce_sum((1 - accept_dist) * initial_dist)
221 num_examples_per_class_seen, math_ops.reduce_sum(
225 math_ops.reduce_sum(num_examples_per_class_seen))
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| /external/tensorflow/tensorflow/python/autograph/impl/ |
| D | api_test.py | 107 while tf.reduce_sum(x) > s:
128 while tf.reduce_sum(x) > s:
150 while tf.reduce_sum(x) > s:
173 while tf.reduce_sum(x) > s:
239 while tf.reduce_sum(x) > s:
686 while tf.reduce_sum(x) > self.a:
714 while tf.reduce_sum(x) > self.a:
892 while tf.reduce_sum(x) > s:
908 while tf.reduce_sum(x) > s:
1036 while tf.reduce_sum(x) > s:
[all …]
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