| /external/clang/test/SemaCXX/ |
| D | warn-consumed-analysis.cpp | 83 ConsumableClass<int> var0;
87 ConsumableClass<int> var4(var0); // copy consumed value
89 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
95 var0 = ConsumableClass<int>(42);
96 *var0;
98 var0 = var1;
99 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
101 if (var0.isValid()) {
102 *var0;
106 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
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| /external/llvm-project/clang/test/SemaCXX/ |
| D | warn-consumed-analysis.cpp | 89 ConsumableClass<int> var0;
93 ConsumableClass<int> var4(var0); // copy consumed value
95 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
101 var0 = ConsumableClass<int>(42);
102 *var0;
104 var0 = var1;
105 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
107 if (var0.isValid()) {
108 *var0;
112 …*var0; // expected-warning {{invalid invocation of method 'operator*' on object 'var0' while it is…
[all …]
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | ftrl_test.py | 35 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
40 return var0, var1, grads0, grads1
43 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
50 ftrl_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
53 self.assertAllClose([0.0, 0.0], self.evaluate(var0))
60 return self.evaluate(var0), self.evaluate(var1)
63 var0, var1, grads0, grads1 = self.initVariableAndGradient(dtype)
65 adagrad_update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
68 self.assertAllClose([0.0, 0.0], self.evaluate(var0))
75 return self.evaluate(var0), self.evaluate(var1)
[all …]
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| D | proximal_gradient_descent_test.py | 36 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0])
42 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
45 self.assertAllClose([0.0, 0.0], self.evaluate(var0))
52 self.assertAllClose(np.array([-0.9, -1.8]), self.evaluate(var0))
57 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
64 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
67 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
74 self.assertAllClose(np.array([0.1, 0.2]), self.evaluate(var0))
79 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
86 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
[all …]
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| D | proximal_adagrad_test.py | 36 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0])
45 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
48 self.assertAllClose([0.0, 0.0], self.evaluate(var0))
56 np.array([-2.60260963, -4.29698515]), self.evaluate(var0))
60 self.assertStartsWith(opt_vars[0].name, var0._shared_name)
66 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
76 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
79 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
85 self.assertAllClose(np.array([-1.60261, -2.296985]), self.evaluate(var0))
90 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0])
[all …]
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| D | adagrad_test.py | 36 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
45 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
53 self.evaluate(var0),
63 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
70 zip([grads0, grads1], [var0, var1]))
73 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
81 self.evaluate(var0),
91 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
99 zip([grads0, grads1], [var0, var1]))
[all …]
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| D | adagrad_da_test.py | 39 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
50 zip([grads0, grads1], [var0, var1]), global_step=global_step)
53 self.assertAllClose([0.0, 0.0], self.evaluate(var0))
66 np.array([-0.904534, -1.603567]), self.evaluate(var0))
75 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
87 zip([grads0, grads1], [var0, var1]), global_step=global_step)
90 self.assertAllCloseAccordingToType([1.0, 2.0], self.evaluate(var0))
97 np.array([-0.904534, -1.603567]), self.evaluate(var0))
106 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
118 zip([grads0, grads1], [var0, var1]), global_step=global_step)
[all …]
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| D | momentum_test.py | 45 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
52 zip([grads0, grads1], [var0, var1]))
56 slot0 = mom_opt.get_slot(var0, "momentum")
57 self.assertEqual(slot0.get_shape(), var0.get_shape())
64 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
77 self.evaluate(var0))
95 ]), self.evaluate(var0))
105 var0 = resource_variable_ops.ResourceVariable([0.1, 0.2], dtype=dtype)
111 cost = 0.4 * var0 * var0 + 0.9 * var1
116 opt_op = mom_op.minimize(cost, global_step, [var0, var1])
[all …]
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| /external/tensorflow/tensorflow/python/training/ |
| D | optimizer_test.py | 46 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype,
51 return 5 * var0 + 3 * var1 # pylint: disable=cell-var-from-loop
60 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
63 opt_op = sgd_op.minimize(loss, global_step, [var0, var1])
66 self.assertAllClose([-14., -13.], self.evaluate(var0))
73 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
75 cost = 5 * var0 + 3 * var1
81 global_step, [var0, var1],
87 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
92 self.assertAllClose([-14., -13.], self.evaluate(var0))
[all …]
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| D | gradient_descent_test.py | 42 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
48 zip([grads0, grads1], [var0, var1]))
51 self.assertAllCloseAccordingToType([1.0, 2.0], self.evaluate(var0))
57 self.evaluate(var0))
66 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
71 zip([grads0, grads1], [var0, var1]))
76 resources.initialize_resources([var0, var1]).run()
78 self.assertAllCloseAccordingToType([1.0, 2.0], self.evaluate(var0))
84 self.evaluate(var0))
92 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
[all …]
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| D | momentum_test.py | 50 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0],
57 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
68 mom_update = mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
73 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
78 slot0 = mom_opt.get_slot(var0, "momentum")
79 self.assertEqual(slot0.get_shape(), var0.get_shape())
97 np.array([1.0 - (0.1 * 2.0), 2.0 - (0.1 * 2.0)]), self.evaluate(var0))
103 mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
118 ]), self.evaluate(var0))
140 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0],
[all …]
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| D | proximal_adagrad_test.py | 40 var0 = variables.Variable([0.0, 0.0])
49 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
52 v0_val, v1_val = self.evaluate([var0, var1])
60 v0_val, v1_val = self.evaluate([var0, var1])
64 self.assertStartsWith(opt_vars[0].name, var0._shared_name)
77 var0 = variables.Variable([1.0, 2.0])
87 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
90 v0_val, v1_val = self.evaluate([var0, var1])
97 v0_val, v1_val = self.evaluate([var0, var1])
105 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
[all …]
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| D | adagrad_test.py | 45 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
48 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
62 zip([grads0, grads1], [var0, var1]))
66 v0_val, v1_val = self.evaluate([var0, var1])
75 ada_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
78 v0_val, v1_val = self.evaluate([var0, var1])
103 var0 = resource_variable_ops.ResourceVariable(
106 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
112 self.evaluate(var0))
117 self.evaluate(var0),
[all …]
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| D | ftrl_test.py | 44 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0],
49 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
58 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
61 v0_val, v1_val = self.evaluate([var0, var1])
69 v0_val, v1_val = self.evaluate([var0, var1])
86 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
96 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
99 v0_val, v1_val = self.evaluate([var0, var1])
106 v0_val, v1_val = self.evaluate([var0, var1])
117 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]],
[all …]
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| D | proximal_gradient_descent_test.py | 41 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0])
44 var0 = variables.Variable([0.0, 0.0])
50 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
53 v0_val, v1_val = self.evaluate([var0, var1])
61 v0_val, v1_val = self.evaluate([var0, var1])
73 var0 = variables.Variable([1.0, 2.0])
80 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
83 v0_val, v1_val = self.evaluate([var0, var1])
91 v0_val, v1_val = self.evaluate([var0, var1])
98 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
[all …]
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| D | adagrad_da_test.py | 42 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
45 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
56 zip([grads0, grads1], [var0, var1]), global_step=global_step)
59 v0_val, v1_val = self.evaluate([var0, var1])
66 v0_val, v1_val = self.evaluate([var0, var1])
88 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
92 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
98 self.assertAllCloseAccordingToType([[1.0, 2.0]], self.evaluate(var0))
103 self.evaluate(var0),
110 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
[all …]
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| D | rmsprop_test.py | 105 var0 = resource_variable_ops.ResourceVariable(var0_np)
108 var0 = variables.Variable(var0_np)
119 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
122 mg0 = opt.get_slot(var0, "mg")
126 rms0 = opt.get_slot(var0, "rms")
130 mom0 = opt.get_slot(var0, "momentum")
143 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
165 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
172 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
174 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
[all …]
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| D | adadelta_test.py | 45 var0 = resource_variable_ops.ResourceVariable(
50 var0 = variables.Variable(var0_init, dtype=dtype)
71 zip([grads, grads], [var0, var1]))
78 self.assertStartsWith(opt_vars[0].name, var0._shared_name)
79 self.assertStartsWith(opt_vars[1].name, var0._shared_name)
88 slot[0] = adadelta_opt.get_slot(var0, "accum")
89 self.assertEqual(slot[0].get_shape(), var0.get_shape())
92 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
93 self.assertEqual(slot_update[0].get_shape(), var0.get_shape())
105 self.assertAllClose(var0_init, self.evaluate(var0))
[all …]
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| D | adam_test.py | 69 var0 = resource_variable_ops.ResourceVariable(var0_np)
72 var0 = variables.RefVariable(var0_np)
83 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
87 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
103 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
173 var0 = resource_variable_ops.ResourceVariable(
178 var0 = variables.RefVariable(var0_np)
194 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
216 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
226 opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
[all …]
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| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | gradient_descent_test.py | 45 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
50 sgd_op = sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
56 self.evaluate(var0))
61 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
66 sgd_op = sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
72 sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
75 self.evaluate(var0))
82 sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
86 self.evaluate(var0))
119 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
[all …]
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| D | ftrl_test.py | 42 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
45 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
54 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
57 v0_val, v1_val = self.evaluate([var0, var1])
65 v0_val, v1_val = self.evaluate([var0, var1])
81 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
91 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
94 v0_val, v1_val = self.evaluate([var0, var1])
101 v0_val, v1_val = self.evaluate([var0, var1])
111 var0 = variables.Variable([[1.0, 2.0]], dtype=dtype)
[all …]
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| D | adagrad_test.py | 80 var0 = variables.Variable(var0_np)
96 zip([grads0, grads1], [var0, var1]))
100 v0_val, v1_val = self.evaluate([var0, var1])
109 ada_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
114 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
131 var0 = variables.Variable(var0_np)
146 zip([grads0, grads1], [var0, var1]))
150 v0_val, v1_val = self.evaluate([var0, var1])
159 ada_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
165 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
[all …]
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| D | rmsprop_test.py | 114 var0 = variables.Variable(var0_np, dtype=dtype)
125 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
129 mg0 = opt.get_slot(var0, "mg")
136 mom0 = opt.get_slot(var0, "momentum")
142 rms0 = opt.get_slot(var0, "rms")
155 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
178 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
189 var0 = variables.Variable(var0_np)
207 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
210 rms0 = opt.get_slot(var0, "rms")
[all …]
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| D | adadelta_test.py | 52 var0 = variables.Variable(var0_init, dtype=dtype)
55 var0 = variables.Variable(var0_init, dtype=dtype)
76 zip([grads, grads], [var0, var1]))
82 slot[0] = adadelta_opt.get_slot(var0, "accum_grad")
83 self.assertEqual(slot[0].shape, var0.shape)
85 slot_update[0] = adadelta_opt.get_slot(var0, "accum_var")
86 self.assertEqual(slot_update[0].shape, var0.shape)
95 self.assertAllClose(var0_init, self.evaluate(var0))
105 adadelta_opt.apply_gradients(zip([grads, grads], [var0, var1]))
137 self.evaluate(var0),
[all …]
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| /external/deqp/external/vulkancts/data/vulkan/glsl/440/ |
| D | linkage.test | 23 layout(location = 0) out vec2 var0;
28 var0 = in0 + in0;
36 layout(location = 0) in vec2 var0;
41 vec2 out0 = var0;
64 layout(location = 0) out vec2 var0;
69 var0 = in0_3 * in0 + in0;
77 layout(location = 0) in vec2 var0;
82 vec2 out0 = var0;
107 layout(location = 0) out vec3 var0;
112 var0 = in0 + in0;
[all …]
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