| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | gradient_correctness_test.py | 36 with test_util.AbstractGradientTape(use_tape=use_tape) as tape:
38 tape.watch(x)
42 grads = tape.gradient([yexp, yexplog], [x])
51 with test_util.AbstractGradientTape(use_tape=use_tape) as tape:
52 tape.watch(x)
53 dx_dx = tape.gradient(x, x)
59 with test_util.AbstractGradientTape(use_tape=use_tape) as tape:
60 tape.watch(x)
61 dx_dx = tape.gradient(x, x)
66 with test_util.AbstractGradientTape(use_tape=use_tape) as tape:
[all …]
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| D | map_ops_test.py | 190 with backprop.GradientTape() as tape:
194 tape.watch(v)
198 g = tape.gradient(l, v)
202 with backprop.GradientTape(persistent=True) as tape:
210 tape.watch(v)
211 tape.watch(v2)
212 tape.watch(v3)
219 g = tape.gradient(l * 5, v)
220 g2 = tape.gradient(l2 * 6, v2)
221 g3 = tape.gradient(l3 * 7, v3)
[all …]
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| D | relu_op_test.py | 151 with backprop.GradientTape() as tape:
152 tape.watch(x)
154 return tape.gradient(y, x)
169 with backprop.GradientTape() as tape:
170 tape.watch(x)
172 return tape.gradient(y, x)
197 with backprop.GradientTape() as tape:
198 tape.watch(x)
200 return tape.gradient(y, x)
340 with backprop.GradientTape() as tape:
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| /external/tensorflow/tensorflow/c/eager/ |
| D | mnist_gradients_testutil.cc | 49 auto tape = new Tape(/*persistent=*/false); in AddGradModel() local
50 tape->Watch(inputs[0]); // Watch x. in AddGradModel()
51 tape->Watch(inputs[1]); // Watch y. in AddGradModel()
53 AbstractContextPtr tape_ctx(new TapeContext(ctx, tape, registry)); in AddGradModel()
56 TF_RETURN_IF_ERROR(tape->ComputeGradient(ctx, /*targets=*/add_outputs, in AddGradModel()
62 delete tape; in AddGradModel()
73 auto tape = new Tape(/*persistent=*/false); in MatMulGradModel() local
74 tape->Watch(inputs[0]); // Watch x. in MatMulGradModel()
75 tape->Watch(inputs[1]); // Watch y. in MatMulGradModel()
77 AbstractContextPtr tape_ctx(new TapeContext(ctx, tape, registry)); in MatMulGradModel()
[all …]
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| D | gradients_test.cc | 78 auto tape = std::make_unique<Tape>(/*persistent=*/false); in IdentityNGradModel() local
79 tape->Watch(inputs[0]); in IdentityNGradModel()
80 tape->Watch(inputs[1]); in IdentityNGradModel()
83 AbstractContextPtr tape_ctx(new TapeContext(ctx, tape.get(), registry)); in IdentityNGradModel()
86 TF_RETURN_IF_ERROR(tape->ComputeGradient(ctx, in IdentityNGradModel()
196 auto tape = std::make_unique<Tape>(/*persistent=*/false); in TEST_P() local
198 &num_retvals, &forward_op, tape.get(), registry); in TEST_P()
210 Tape tape(/*persistent=*/false); in RecordOperationWithNullGradientFunctionModel() local
211 tape.Watch(inputs[0]); in RecordOperationWithNullGradientFunctionModel()
214 tape.RecordOperation(inputs, neg_outputs, nullptr, "Neg"); in RecordOperationWithNullGradientFunctionModel()
[all …]
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| /external/tensorflow/tensorflow/python/eager/ |
| D | tape.py | 40 def __init__(self, tape): argument
41 self._tape = tape
49 tape = pywrap_tfe.TFE_Py_TapeSetNew(persistent, watch_accessed_variables)
50 return Tape(tape)
53 def push_tape(tape): argument
55 pywrap_tfe.TFE_Py_TapeSetAdd(tape._tape) # pylint: disable=protected-access
58 def watch(tape, tensor): argument
60 pywrap_tfe.TFE_Py_TapeWatch(tape._tape, tensor) # pylint: disable=protected-access
95 def watch_variable(tape, variable): argument
104 pywrap_tfe.TFE_Py_TapeWatchVariable(tape._tape, var) # pylint: disable=protected-access
[all …]
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| D | pywrap_tfe_test.py | 93 with backprop.GradientTape(persistent=True) as tape:
95 tape.watch(a_2_by_2)
99 dz_dy = tape.gradient(z, [a_2_by_2])[0]
109 with backprop.GradientTape(persistent=True) as tape:
112 tape.watch(m)
116 dz_dy = tape.gradient(z, [m])[0]
145 with backprop.GradientTape(persistent=True) as tape:
146 tape.watch(a_2_by_2)
147 tape.watch(b_2_by_2)
151 dz1_dy = tape.gradient(z1, [a_2_by_2])[0]
[all …]
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| D | backprop_test.py | 29 from tensorflow.python.eager import tape as tape_lib
407 with backprop.GradientTape(persistent=True) as tape:
408 tape.watch(a_2_by_2)
409 dy_dy = tape.gradient(a_2_by_2, [a_2_by_2])[0]
416 with backprop.GradientTape(persistent=True) as tape:
417 tape.watch(a_2_by_2)
418 dy_dy = tape.gradient([a_2_by_2, a_2_by_2], [a_2_by_2])[0]
1360 with backprop.GradientTape() as tape:
1361 tape.watch(x)
1365 return self.evaluate(tape.gradient(y, x))
[all …]
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| D | pywrap_tfe.h | 159 void TFE_Py_TapeSetRemove(PyObject* tape);
162 void TFE_Py_TapeSetAdd(PyObject* tape);
179 void TFE_Py_TapeWatch(PyObject* tape, PyObject* tensor);
246 void TFE_Py_TapeWatchVariable(PyObject* tape, PyObject* variable);
253 PyObject* TFE_Py_TapeGradient(PyObject* tape, PyObject* target,
285 PyObject* TFE_Py_TapeWatchedVariables(PyObject* tape);
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| D | forwardprop_test.py | 33 from tensorflow.python.eager import tape as tape_lib
114 with backprop.GradientTape() as tape:
115 tape.watch(params)
117 return tape.gradient(
147 with backprop.GradientTape() as tape:
148 tape.watch(primals)
151 return acc.jvp(tape.gradient(f_out, primals))
694 with backprop.GradientTape() as tape:
697 tape.watch(c)
709 self.assertIsNone(tape.gradient(d, c))
[all …]
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| D | function_gradients_test.py | 108 with backprop.GradientTape(persistent=persistent) as tape:
109 tape.watch(x)
114 tape_dy = tape.gradient(y, x)
134 with backprop.GradientTape() as tape:
135 tape.watch(primal)
137 return tape.gradient(primal_out, primal)
158 with backprop.GradientTape() as tape:
160 g, = tape.gradient(primal_out, tape.watched_variables())
186 with backprop.GradientTape(persistent=True) as tape:
188 tape.watch(start)
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| /external/llvm-project/clang/test/SemaCXX/ |
| D | constexpr-turing-cxx2a.cpp | 8 bool tape; member
37 Tape *tape = new Tape; in run() local
42 auto [val, dir, next_state] = tm[state][tape->val]; in run()
43 tape->val = val; in run()
44 tape = (dir == L ? tape->left() : tape->right()); in run()
48 delete tape; in run()
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| D | constexpr-turing.cpp | 10 bool tape; member
35 constexpr unsigned run(const State *tm, const Tape &tape, unsigned state) { in run() argument
37 run(tm, move(update(tape, tm[state][tape.val].tape), in run()
38 tm[state][tape.val].dir), in run()
39 tm[state][tape.val].next) + 1; in run()
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| /external/tensorflow/tensorflow/python/framework/experimental/ |
| D | unified_api_test.py | 35 from tensorflow.python.framework.experimental import tape as tape_lib
91 with tape_lib.GradientTape() as tape:
92 tape.watch(a)
93 tape.watch(b)
95 grads = tape.gradient(result, [a, b])
145 with tape_lib.GradientTape() as tape:
146 tape.watch(t)
148 grads = tape.gradient(result, t)
195 with tape_lib.GradientTape() as tape:
196 tape.watch(a)
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| /external/clang/test/SemaCXX/ |
| D | constexpr-turing.cpp | 10 bool tape; member
35 constexpr unsigned run(const State *tm, const Tape &tape, unsigned state) { in run() argument
37 run(tm, move(update(tape, tm[state][tape.val].tape), in run()
38 tm[state][tape.val].dir), in run()
39 tm[state][tape.val].next) + 1; in run()
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| /external/tensorflow/tensorflow/c/experimental/gradients/ |
| D | nn_grad_test.cc | 44 Tape tape(/*persistent=*/false); in ReluGradModel() local
45 tape.Watch(inputs[0]); in ReluGradModel()
47 AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, registry)); in ReluGradModel()
51 TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, /*targets=*/temp_outputs, in ReluGradModel()
84 Tape tape(/*persistent=*/false); in SparseSoftmaxCrossEntropyWithLogitsGradModel() local
85 tape.Watch(inputs[0]); // Watch score. in SparseSoftmaxCrossEntropyWithLogitsGradModel()
86 tape.Watch(inputs[1]); // Watch label. in SparseSoftmaxCrossEntropyWithLogitsGradModel()
88 AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, registry)); in SparseSoftmaxCrossEntropyWithLogitsGradModel()
93 TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, /*targets=*/temp_outputs, in SparseSoftmaxCrossEntropyWithLogitsGradModel()
114 Tape tape(/*persistent=*/false); in BiasAddGradModel() local
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| D | custom_gradient_test.cc | 71 Tape tape(/*persistent=*/false); in ExpWithPassThroughGrad() local
72 tape.Watch(inputs[0]); // Watch x. in ExpWithPassThroughGrad()
77 tape.RecordOperation(inputs, exp_outputs, gradient_function.release()); in ExpWithPassThroughGrad()
78 TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, in ExpWithPassThroughGrad()
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| /external/tensorflow/tensorflow/python/ops/ |
| D | array_ops_test.py | 40 with backprop.GradientTape() as tape:
41 tape.watch(x)
43 grad_a = tape.gradient(a, x)
44 with backprop.GradientTape() as tape:
45 tape.watch(x)
47 grad_b = tape.gradient(b, x)
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| /external/tensorflow/tensorflow/python/distribute/ |
| D | custom_training_loop_gradient_test.py | 80 with backprop.GradientTape() as tape:
81 tape.watch(x) # Manually watch non-variable tensors.
83 grads = tape.gradient(y, x)
107 with backprop.GradientTape() as tape:
108 tape.watch(x) # Manually watch non-variable tensors.
110 grads = tape.gradient(y, x)
140 with backprop.GradientTape() as tape:
142 return tape.gradient(y, x)
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| /external/tensorflow/tensorflow/python/keras/integration_test/ |
| D | forwardprop_test.py | 61 with tf.GradientTape() as tape:
62 tape.watch(params)
64 return tape.gradient(
75 with tf.GradientTape() as tape:
76 tape.watch(primals)
79 return acc.jvp(tape.gradient(f_out, primals))
211 with tf.GradientTape() as tape:
213 tape.watch(input_value)
215 jac_back = tape.jacobian(output,
252 with tf.GradientTape() as tape:
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| D | gradients_test.py | 49 with tf.GradientTape(persistent=True) as tape:
50 tape.watch(vars_to_grad)
54 grads_re = tape.gradient(out_re, vars_to_grad)
55 grads = tape.gradient(out, vars_to_grad)
96 with tf.GradientTape() as tape:
97 tape.watch(x)
99 return tape.batch_jacobian(y, x)
|
| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | custom_training_loop_models_test.py | 79 with backprop.GradientTape() as tape:
82 grads = tape.gradient(loss, model.variables)
104 with backprop.GradientTape() as tape:
107 grads = tape.gradient(loss, model.variables)
142 with backprop.GradientTape() as tape:
145 grads = tape.gradient(loss, model.variables)
167 with backprop.GradientTape() as tape:
170 grads = tape.gradient(loss, model.variables)
199 with backprop.GradientTape() as tape:
202 grads = tape.gradient(loss, model.variables)
[all …]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | eager_test.py | 61 with backprop.GradientTape(persistent=True) as tape:
62 tape.watch(x)
63 tape.watch(y)
65 da_dx = tape.gradient(a, x)
66 da_dy = tape.gradient(a, y)
267 with backprop.GradientTape() as tape:
269 dy_dx = tape.gradient(y, x)
281 with backprop.GradientTape() as tape:
284 dy_dx = tape.gradient(y, embedding_matrix)
491 with backprop.GradientTape() as tape:
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| /external/tensorflow/tensorflow/python/keras/tests/ |
| D | tracking_util_test.py | 116 with backprop.GradientTape() as tape:
119 gradients = tape.gradient(loss, variables)
124 with backprop.GradientTape() as tape:
127 gradients = tape.gradient(loss, variables)
206 with backprop.GradientTape() as tape:
209 gradients = tape.gradient(loss, variables)
283 with backprop.GradientTape() as tape:
286 gradients = tape.gradient(loss, variables)
305 with backprop.GradientTape() as tape:
308 gradients = tape.gradient(loss, variables)
[all …]
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| D | memory_test.py | 69 with backprop.GradientTape() as tape:
72 tape.gradient(result, net.variables)
74 del tape
|