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Searched refs:var0 (Results 1 – 25 of 75) sorted by relevance

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/external/clang/test/SemaCXX/
Dwarn-consumed-analysis.cpp83 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/tensorflow/tensorflow/python/training/
Doptimizer_test.py42 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype,
47 return 5 * var0 + 3 * var1 # pylint: disable=cell-var-from-loop
56 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
59 opt_op = sgd_op.minimize(loss, global_step, [var0, var1])
62 self.assertAllClose([-14., -13.], self.evaluate(var0))
69 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
71 cost = 5 * var0 + 3 * var1
77 global_step, [var0, var1],
83 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
88 self.assertAllClose([-14., -13.], self.evaluate(var0))
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Dgradient_descent_test.py43 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
49 zip([grads0, grads1], [var0, var1]))
52 self.assertAllCloseAccordingToType([1.0, 2.0], self.evaluate(var0))
58 self.evaluate(var0))
67 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
72 zip([grads0, grads1], [var0, var1]))
77 resources.initialize_resources([var0, var1]).run()
79 self.assertAllCloseAccordingToType([1.0, 2.0], self.evaluate(var0))
85 self.evaluate(var0))
93 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
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Dmomentum_test.py50 var0 = resource_variable_ops.ResourceVariable(
55 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
67 zip([grads0, grads1], [var0, var1]))
72 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
77 slot0 = mom_opt.get_slot(var0, "momentum")
78 self.assertEquals(slot0.get_shape(), var0.get_shape())
97 self.evaluate(var0))
103 mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
118 ]), self.evaluate(var0))
140 var0 = resource_variable_ops.ResourceVariable(
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Dproximal_adagrad_test.py40 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)
79 var0 = variables.Variable([1.0, 2.0])
89 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
92 v0_val, v1_val = self.evaluate([var0, var1])
99 v0_val, v1_val = self.evaluate([var0, var1])
107 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
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Dadagrad_test.py45 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),
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Dftrl_test.py44 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
47 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
56 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
59 v0_val, v1_val = self.evaluate([var0, var1])
67 v0_val, v1_val = self.evaluate([var0, var1])
85 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
95 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
98 v0_val, v1_val = self.evaluate([var0, var1])
105 v0_val, v1_val = self.evaluate([var0, var1])
115 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
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Dproximal_gradient_descent_test.py42 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0])
45 var0 = variables.Variable([0.0, 0.0])
51 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
54 v0_val, v1_val = self.evaluate([var0, var1])
62 v0_val, v1_val = self.evaluate([var0, var1])
77 var0 = variables.Variable([1.0, 2.0])
84 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
87 v0_val, v1_val = self.evaluate([var0, var1])
95 v0_val, v1_val = self.evaluate([var0, var1])
103 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
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Dadagrad_da_test.py41 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
44 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
55 zip([grads0, grads1], [var0, var1]), global_step=global_step)
58 v0_val, v1_val = self.evaluate([var0, var1])
65 v0_val, v1_val = self.evaluate([var0, var1])
89 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
93 pred = math_ops.matmul(embedding_ops.embedding_lookup([var0], [0]), x)
99 self.assertAllCloseAccordingToType([[1.0, 2.0]], self.evaluate(var0))
104 self.evaluate(var0),
112 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
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Drmsprop_test.py105 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)
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Dadadelta_test.py45 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.assertEquals(slot[0].get_shape(), var0.get_shape())
92 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
93 self.assertEquals(slot_update[0].get_shape(), var0.get_shape())
105 self.assertAllClose(var0_init, self.evaluate(var0))
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Dadam_test.py68 var0 = resource_variable_ops.ResourceVariable(var0_np)
71 var0 = variables.RefVariable(var0_np)
82 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
86 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
102 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
172 var0 = resource_variable_ops.ResourceVariable(
177 var0 = variables.RefVariable(var0_np)
193 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
215 self.assertAllClose([1.0, 2.0], self.evaluate(var0))
225 opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
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/external/tensorflow/tensorflow/compiler/tests/
Dftrl_test.py35 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)
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Dproximal_gradient_descent_test.py36 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]))
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Dproximal_adagrad_test.py36 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])
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Dadagrad_test.py36 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]))
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Dmomentum_test.py45 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.assertEquals(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])
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Dadagrad_da_test.py39 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)
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Dadadelta_test.py49 var0 = resource_variable_ops.ResourceVariable(
65 zip([grads, grads], [var0, var1]))
68 self.assertStartsWith(opt_vars[0].name, var0._shared_name)
69 self.assertStartsWith(opt_vars[1].name, var0._shared_name)
78 slot[0] = adadelta_opt.get_slot(var0, "accum")
79 self.assertEqual(slot[0].get_shape(), var0.get_shape())
82 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
83 self.assertEqual(slot_update[0].get_shape(), var0.get_shape())
95 self.assertAllClose(var0_init, self.evaluate(var0))
130 self.evaluate(var0),
/external/tensorflow/tensorflow/python/keras/optimizer_v2/
Dgradient_descent_test.py45 var0 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
50 sgd_op = sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
56 self.evaluate(var0))
61 var0 = resource_variable_ops.ResourceVariable([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 = resource_variable_ops.ResourceVariable([1.0, 2.0], dtype=dtype)
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Dftrl_test.py43 var0 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
46 var0 = variables.Variable([0.0, 0.0], dtype=dtype)
55 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
58 v0_val, v1_val = self.evaluate([var0, var1])
66 v0_val, v1_val = self.evaluate([var0, var1])
84 var0 = variables.Variable([1.0, 2.0], dtype=dtype)
94 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
97 v0_val, v1_val = self.evaluate([var0, var1])
104 v0_val, v1_val = self.evaluate([var0, var1])
114 var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
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Dadagrad_test.py79 var0 = resource_variable_ops.ResourceVariable(var0_np)
95 zip([grads0, grads1], [var0, var1]))
99 v0_val, v1_val = self.evaluate([var0, var1])
108 ada_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
113 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
130 var0 = resource_variable_ops.ResourceVariable(var0_np)
145 zip([grads0, grads1], [var0, var1]))
149 v0_val, v1_val = self.evaluate([var0, var1])
158 ada_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
164 self.assertAllCloseAccordingToType(var0_np, self.evaluate(var0))
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Drmsprop_test.py114 var0 = resource_variable_ops.ResourceVariable(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))
188 var0 = resource_variable_ops.ResourceVariable(var0_np)
206 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
209 rms0 = opt.get_slot(var0, "rms")
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Dadadelta_test.py50 var0 = resource_variable_ops.ResourceVariable(
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),
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/external/deqp/external/vulkancts/data/vulkan/glsl/440/
Dlinkage.test23 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;
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