| /external/tensorflow/tensorflow/python/ops/ |
| D | gradients_test.py | 46 from tensorflow.python.ops import gradients
72 w_grad = gradients.gradients(h, w)[0]
85 gw = gradients.gradients(c, [w])[0]
94 gw = gradients.gradients(wx, [w], colocate_gradients_with_ops=True)[0]
108 gw1 = gradients.gradients(z, [w], colocate_gradients_with_ops=True)[0]
111 gw2 = gradients.gradients(z, [w], colocate_gradients_with_ops=False)[0]
127 gw1 = gradients.gradients(z, [w], colocate_gradients_with_ops=True)[0]
130 gw2 = gradients.gradients(z, [w], colocate_gradients_with_ops=False)[0]
144 gz_x = gradients.gradients(z, [x], colocate_gradients_with_ops=True,
159 grads = gradients.gradients(z, [x])
[all …]
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| /external/skqp/tools/lua/ |
| D | gradients.lua | 24 gradients = {}
35 gradients[i] = {}
37 gradients[i].filename = filename
47 gradients[i].boundsWidth = width
48 gradients[i].boundsHeight = height
50 gradients[i].colorCount = g.colorCount
51 gradients[i].type = g.type
52 gradients[i].tile = g.tile
60 gradients[i].isEvenlySpaced = isEvenlySpaced
68 gradients[i].numHardStops = numHardStops
[all …]
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| /external/skia/tools/lua/ |
| D | gradients.lua | 24 gradients = {}
35 gradients[i] = {}
37 gradients[i].filename = filename
47 gradients[i].boundsWidth = width
48 gradients[i].boundsHeight = height
50 gradients[i].colorCount = g.colorCount
51 gradients[i].type = g.type
52 gradients[i].tile = g.tile
60 gradients[i].isEvenlySpaced = isEvenlySpaced
68 gradients[i].numHardStops = numHardStops
[all …]
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/ops/ |
| D | stats_accumulator_ops.py | 44 (stamp_token, num_updates, partition_ids, feature_ids, gradients,
55 saver.BaseSaverBuilder.SaveSpec(gradients, slice_spec,
73 gradients, hessians): argument
78 feature_ids, gradients, hessians)
82 feature_ids, gradients, hessians)
101 gradients=restored_tensors[4],
196 def add(self, stamp_token, partition_ids, feature_ids, gradients, hessians): argument
198 partition_ids, feature_ids, gradients, hessians = (self._make_summary(
199 partition_ids, feature_ids, gradients, hessians))
203 [gradients], [hessians])
[all …]
|
| /external/skqp/gn/ |
| D | effects.gni | 37 "$_src/shaders/gradients/Sk4fGradientBase.cpp",
38 "$_src/shaders/gradients/Sk4fGradientBase.h",
39 "$_src/shaders/gradients/Sk4fGradientPriv.h",
40 "$_src/shaders/gradients/Sk4fLinearGradient.cpp",
41 "$_src/shaders/gradients/Sk4fLinearGradient.h",
42 "$_src/shaders/gradients/SkGradientShader.cpp",
43 "$_src/shaders/gradients/SkGradientShaderPriv.h",
44 "$_src/shaders/gradients/SkLinearGradient.cpp",
45 "$_src/shaders/gradients/SkLinearGradient.h",
46 "$_src/shaders/gradients/SkRadialGradient.cpp",
[all …]
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| D | sksl.gni | 48 "$_src/gpu/gradients/GrDualIntervalGradientColorizer.fp",
49 "$_src/gpu/gradients/GrSingleIntervalGradientColorizer.fp",
50 "$_src/gpu/gradients/GrTextureGradientColorizer.fp",
51 "$_src/gpu/gradients/GrUnrolledBinaryGradientColorizer.fp",
52 "$_src/gpu/gradients/GrLinearGradientLayout.fp",
53 "$_src/gpu/gradients/GrRadialGradientLayout.fp",
54 "$_src/gpu/gradients/GrSweepGradientLayout.fp",
55 "$_src/gpu/gradients/GrTwoPointConicalGradientLayout.fp",
56 "$_src/gpu/gradients/GrClampedGradientEffect.fp",
57 "$_src/gpu/gradients/GrTiledGradientEffect.fp",
|
| /external/skia/gn/ |
| D | effects.gni | 37 "$_src/shaders/gradients/Sk4fGradientBase.cpp",
38 "$_src/shaders/gradients/Sk4fGradientBase.h",
39 "$_src/shaders/gradients/Sk4fGradientPriv.h",
40 "$_src/shaders/gradients/Sk4fLinearGradient.cpp",
41 "$_src/shaders/gradients/Sk4fLinearGradient.h",
42 "$_src/shaders/gradients/SkGradientShader.cpp",
43 "$_src/shaders/gradients/SkGradientShaderPriv.h",
44 "$_src/shaders/gradients/SkLinearGradient.cpp",
45 "$_src/shaders/gradients/SkLinearGradient.h",
46 "$_src/shaders/gradients/SkRadialGradient.cpp",
[all …]
|
| D | sksl.gni | 49 "$_src/gpu/gradients/GrDualIntervalGradientColorizer.fp",
50 "$_src/gpu/gradients/GrSingleIntervalGradientColorizer.fp",
51 "$_src/gpu/gradients/GrTextureGradientColorizer.fp",
52 "$_src/gpu/gradients/GrUnrolledBinaryGradientColorizer.fp",
53 "$_src/gpu/gradients/GrLinearGradientLayout.fp",
54 "$_src/gpu/gradients/GrRadialGradientLayout.fp",
55 "$_src/gpu/gradients/GrSweepGradientLayout.fp",
56 "$_src/gpu/gradients/GrTwoPointConicalGradientLayout.fp",
57 "$_src/gpu/gradients/GrClampedGradientEffect.fp",
58 "$_src/gpu/gradients/GrTiledGradientEffect.fp",
|
| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_FakeQuantWithMinMaxVarsPerChannelGradient.pbtxt | 4 name: "gradients"
6 Backpropagated gradients above the FakeQuantWithMinMaxVars operation,
14 same as `gradients`.
21 Backpropagated gradients w.r.t. inputs, shape same as
23 `gradients * (inputs >= min && inputs <= max)`.
29 Backpropagated gradients w.r.t. min parameter, shape `[d]`:
30 `sum_per_d(gradients * (inputs < min))`.
36 Backpropagated gradients w.r.t. max parameter, shape `[d]`:
37 `sum_per_d(gradients * (inputs > max))`.
52 summary: "Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation."
|
| D | api_def_FakeQuantWithMinMaxVarsGradient.pbtxt | 4 name: "gradients"
6 Backpropagated gradients above the FakeQuantWithMinMaxVars operation.
19 Backpropagated gradients w.r.t. inputs:
20 `gradients * (inputs >= min && inputs <= max)`.
26 Backpropagated gradients w.r.t. min parameter:
27 `sum(gradients * (inputs < min))`.
33 Backpropagated gradients w.r.t. max parameter:
34 `sum(gradients * (inputs > max))`.
49 summary: "Compute gradients for a FakeQuantWithMinMaxVars operation."
|
| D | api_def_SparseAccumulatorTakeGradient.pbtxt | 12 Number of gradients required before we return an aggregate.
18 Indices of the average of the accumulated sparse gradients.
24 Values of the average of the accumulated sparse gradients.
30 Shape of the average of the accumulated sparse gradients.
36 The data type of accumulated gradients. Needs to correspond to the type
43 gradients have been accumulated. If the accumulator has already
44 aggregated more than num_required gradients, it will return its
45 average of the accumulated gradients. Also automatically increments
|
| D | api_def_EluGrad.pbtxt | 5 name: "gradients"
7 The backpropagated gradients to the corresponding Elu operation.
19 The gradients: `gradients * (outputs + 1)` if outputs < 0,
20 `gradients` otherwise.
23 summary: "Computes gradients for the exponential linear (Elu) operation."
|
| D | api_def_SeluGrad.pbtxt | 5 name: "gradients"
7 The backpropagated gradients to the corresponding Selu operation.
19 The gradients: `gradients * (outputs + scale * alpha)`
20 if outputs < 0, `scale * gradients` otherwise.
23 summary: "Computes gradients for the scaled exponential linear (Selu) operation."
|
| D | api_def_FakeQuantWithMinMaxArgsGradient.pbtxt | 4 name: "gradients"
6 Backpropagated gradients above the FakeQuantWithMinMaxArgs operation.
18 Backpropagated gradients below the FakeQuantWithMinMaxArgs operation:
19 `gradients * (inputs >= min && inputs <= max)`.
22 summary: "Compute gradients for a FakeQuantWithMinMaxArgs operation."
|
| D | api_def_AccumulatorTakeGradient.pbtxt | 12 Number of gradients required before we return an aggregate.
18 The average of the accumulated gradients.
24 The data type of accumulated gradients. Needs to correspond to the type
31 gradients have been accumulated. If the accumulator has already
32 aggregated more than num_required gradients, it returns the average of
33 the accumulated gradients. Also automatically increments the recorded
|
| D | api_def_SoftsignGrad.pbtxt | 5 name: "gradients"
7 The backpropagated gradients to the corresponding softsign operation.
19 The gradients: `gradients / (1 + abs(features)) ** 2`.
22 summary: "Computes softsign gradients for a softsign operation."
|
| /external/tensorflow/tensorflow/python/ops/parallel_for/ |
| D | gradients_test.py | 38 from tensorflow.python.ops import gradients as gradient_ops
47 from tensorflow.python.ops.parallel_for import gradients
107 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)
108 while_jacobian = gradients.batch_jacobian(output, inp, use_pfor=False)
115 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)
116 while_jacobian = gradients.batch_jacobian(output, inp, use_pfor=False)
123 pfor_jacobian = gradients.batch_jacobian(final_state.c, inp, use_pfor=True)
128 gradient_ops.gradients(array_ops.gather(final_state.c, i, axis=1), inp)[0]
136 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)
138 pfor_hessian = gradients.batch_jacobian(pfor_jacobian, inp, use_pfor=True)
[all …]
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/ |
| D | split_handler_ops_test.py | 45 gradients = array_ops.constant([2.4, -0.6, 8.0])
53 gradients=gradients,
118 gradients = array_ops.constant([[2.4, 3.0], [-0.6, 0.1], [8.0, 1.0]])
127 gradients=gradients,
159 gradients = array_ops.constant([])
167 gradients=gradients,
200 gradients = array_ops.constant([1.8, 2.4, 0.4, 8.0, 8.0])
208 gradients=gradients,
285 gradients = array_ops.constant([1.8, 8.0])
293 gradients=gradients,
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | gradient_correctness_test.py | 39 grads = gradients_impl.gradients([yexp, yexplog], [x])
48 dx_dx, = gradients_impl.gradients(x, x)
55 dx_dx, = gradients_impl.gradients(x, x)
64 dy_dx, = gradients_impl.gradients(y, x)
73 dy_dx, = gradients_impl.gradients(y, x)
81 dy_dk, = gradients_impl.gradients(y, k)
88 dm_dk, = gradients_impl.gradients(m, k)
95 dm_dk, = gradients_impl.gradients(m, k)
103 dn_dk, = gradients_impl.gradients(n, k)
110 grad_1, = gradients_impl.gradients(k * k, k)
[all …]
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| D | while_v2_test.py | 53 grad = gradients_impl.gradients(ret, [x])
63 grad = gradients_impl.gradients(ret, [x])
116 grad = gradients_impl.gradients(ret, [x]) # [2*x*y]
137 gradx_0 = gradients_impl.gradients(ret[0], [x]) # [2*x*y + y**2]
138 gradx_1 = gradients_impl.gradients(ret[1], [x]) # [y + 1]
139 gradx_2 = gradients_impl.gradients(ret, [x]) # [2*x*y + y**2 + 2*y + 1]
140 grady_0 = gradients_impl.gradients(ret[0], [y]) # [2*x*y + x**2]
141 grady_1 = gradients_impl.gradients(ret[1], [y]) # [x + 1]
142 grady_2 = gradients_impl.gradients(ret, [y]) # [2*x*y + x**2 + x + 1]
173 grad = gradients_impl.gradients(ret2, [x]) # 4x**3
[all …]
|
| /external/tensorflow/tensorflow/core/kernels/ |
| D | relu_op_functor.h | 48 void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients, in operator()
55 gradients * (features > static_cast<T>(0)).template cast<T>(); in operator()
81 void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients, in operator()
88 backprops.device(d) = gradients * ((features > static_cast<T>(0)) * in operator()
116 void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients, in operator()
120 (features > static_cast<T>(0)).select(gradients, gradients * alpha); in operator()
149 void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients, in operator()
154 .select((activations + static_cast<T>(1)) * gradients, gradients); in operator()
187 void operator()(const Device& d, typename TTypes<T>::ConstTensor gradients, in operator()
194 .select(gradients * (activations + scale_alpha), gradients * scale); in operator()
|
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | optimizers.py | 238 gradients = opt.compute_gradients(
245 gradients = _add_scaled_noise_to_gradients(gradients,
250 gradients = _multiply_gradients(gradients, gradient_multipliers)
251 if not gradients:
258 clip_ops.global_norm(list(zip(*gradients))[0]))
262 gradients = _clip_gradients_by_norm(gradients, clip_gradients)
264 gradients = clip_gradients(gradients)
274 for gradient, variable in gradients:
291 clip_ops.global_norm(list(zip(*gradients))[0]))
295 gradients,
[all …]
|
| /external/tensorflow/tensorflow/cc/ |
| D | BUILD | 14 "framework/gradients.h",
35 name = "gradients",
37 "framework/gradients.cc",
41 hdrs = ["framework/gradients.h"],
65 ":gradients",
86 ":gradients",
106 ":gradients",
147 srcs = ["gradients/grad_testutil.cc"],
148 hdrs = ["gradients/grad_testutil.h"],
323 srcs = ["gradients/array_grad.cc"],
[all …]
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/lib/learner/batch/ |
| D | ordinal_split_handler.py | 223 def update_stats(self, stamp_token, example_partition_ids, gradients, argument
250 feature_ids, gradients, hessians) = dense_make_stats_update(
252 example_partition_ids, gradients, hessians, weights, empty_gradients,
259 example_partition_ids, feature_ids, gradients, hessians)
307 num_minibatches, partition_ids, bucket_ids, gradients, hessians = (
311 num_minibatches, partition_ids, bucket_ids, gradients, hessians = (
328 gradients=gradients,
400 def update_stats(self, stamp_token, example_partition_ids, gradients, argument
426 example_partition_ids, feature_ids, gradients,
431 example_partition_ids, gradients, hessians, weights, empty_gradients,
[all …]
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| /external/tensorflow/tensorflow/contrib/compiler/ |
| D | jit_test.py | 27 from tensorflow.python.ops import gradients
181 x_grads = gradients.gradients([y_c], [x])[0]
211 grad_a1 = gradients.gradients(a1t, a1, name="GA")[0]
212 grad_a2 = gradients.gradients(a2t, a2, name="GB")[0]
233 grad_a1 = gradients.gradients(a1t, a1, name="GA")[0]
234 grad_a2 = gradients.gradients(a2t, a2, name="GB")[0]
252 g_r = gradients.gradients(r, x, name="GA")[0]
280 g_r = gradients.gradients(r, x, name="GA")[0]
|