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/external/clang/test/SemaCXX/
Dwarn-consumed-analysis.cpp84 ConsumableClass<int> var1 = ConsumableClass<int>();
90 …*var1; // expected-warning {{invalid invocation of method 'operator*' on object 'var1' while it is…
98 var0 = var1;
103 *var1;
129 ConsumableClass<int> var1(42);
132 *var1;
134 var0 = static_cast<ConsumableClass<int>&&>(var1);
137 …*var1; // expected-warning {{invalid invocation of method 'operator*' on object 'var1' while it is…
175 ConsumableClass<int> var0, var1, var2;
177 if (var0 && var1) {
[all …]
/external/llvm-project/clang/test/SemaCXX/
Dwarn-consumed-analysis.cpp90 ConsumableClass<int> var1 = ConsumableClass<int>();
96 …*var1; // expected-warning {{invalid invocation of method 'operator*' on object 'var1' while it is…
104 var0 = var1;
109 *var1;
148 ConsumableClass<int> var1(42);
151 *var1;
153 var0 = static_cast<ConsumableClass<int>&&>(var1);
156 …*var1; // expected-warning {{invalid invocation of method 'operator*' on object 'var1' while it is…
194 ConsumableClass<int> var0, var1, var2;
196 if (var0 && var1) {
[all …]
/external/tensorflow/tensorflow/compiler/tests/
Dftrl_test.py36 var1 = 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]))
54 self.assertAllClose([0.0, 0.0], self.evaluate(var1))
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]))
69 self.assertAllClose([0.0, 0.0], self.evaluate(var1))
75 return self.evaluate(var0), self.evaluate(var1)
[all …]
Dproximal_gradient_descent_test.py37 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0])
42 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
46 self.assertAllClose([0.0, 0.0], self.evaluate(var1))
53 self.assertAllClose(np.array([-0.09, -0.18]), self.evaluate(var1))
58 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0])
64 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
68 self.assertAllClose([4.0, 3.0], self.evaluate(var1))
75 self.assertAllClose(np.array([3.91, 2.82]), self.evaluate(var1))
80 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0])
86 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
[all …]
Dproximal_adagrad_test.py37 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0])
45 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
49 self.assertAllClose([0.0, 0.0], self.evaluate(var1))
58 np.array([-0.28432083, -0.56694895]), self.evaluate(var1))
61 self.assertStartsWith(opt_vars[1].name, var1._shared_name)
67 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0])
76 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
80 self.assertAllClose([4.0, 3.0], self.evaluate(var1))
86 self.assertAllClose(np.array([3.715679, 2.433051]), self.evaluate(var1))
91 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0])
[all …]
Dadagrad_test.py37 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
42 zip([grads0, grads1], [var0, var1]))
46 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
57 self.evaluate(var1),
64 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
70 zip([grads0, grads1], [var0, var1]))
74 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
85 self.evaluate(var1),
92 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
99 zip([grads0, grads1], [var0, var1]))
[all …]
Dadagrad_da_test.py40 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
50 zip([grads0, grads1], [var0, var1]), global_step=global_step)
54 self.assertAllClose([0.0, 0.0], self.evaluate(var1))
68 np.array([-0.094821, -0.189358]), self.evaluate(var1))
76 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0], dtype=dtype)
87 zip([grads0, grads1], [var0, var1]), global_step=global_step)
91 self.assertAllCloseAccordingToType([4.0, 3.0], self.evaluate(var1))
99 np.array([-0.094821, -0.189358]), self.evaluate(var1))
107 var1 = resource_variable_ops.ResourceVariable([4.0, 3.0], dtype=dtype)
118 zip([grads0, grads1], [var0, var1]), global_step=global_step)
[all …]
Dmomentum_test.py46 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
52 zip([grads0, grads1], [var0, var1]))
59 slot1 = mom_opt.get_slot(var1, "momentum")
60 self.assertEqual(slot1.get_shape(), var1.get_shape())
65 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
80 self.evaluate(var1))
100 ]), self.evaluate(var1))
106 var1 = resource_variable_ops.ResourceVariable([0.3, 0.4], dtype=dtype)
111 cost = 0.4 * var0 * var0 + 0.9 * var1
116 opt_op = mom_op.minimize(cost, global_step, [var0, var1])
[all …]
Dadadelta_test.py51 var1 = resource_variable_ops.ResourceVariable(
65 zip([grads, grads], [var0, var1]))
70 self.assertStartsWith(opt_vars[2].name, var1._shared_name)
71 self.assertStartsWith(opt_vars[3].name, var1._shared_name)
86 slot[1] = adadelta_opt.get_slot(var1, "accum")
87 self.assertEqual(slot[1].get_shape(), var1.get_shape())
90 slot_update[1] = adadelta_opt.get_slot(var1, "accum_update")
91 self.assertEqual(slot_update[1].get_shape(), var1.get_shape())
96 self.assertAllClose(var1_init, self.evaluate(var1))
137 self.evaluate(var1),
/external/tensorflow/tensorflow/python/training/
Doptimizer_test.py48 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype,
51 return 5 * var0 + 3 * var1 # pylint: disable=cell-var-from-loop
61 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
63 opt_op = sgd_op.minimize(loss, global_step, [var0, var1])
67 self.assertAllClose([-6., -5.], self.evaluate(var1))
74 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
75 cost = 5 * var0 + 3 * var1
81 global_step, [var0, var1],
88 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
93 self.assertAllClose([-6., -5.], self.evaluate(var1))
[all …]
Dgradient_descent_test.py43 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
48 zip([grads0, grads1], [var0, var1]))
52 self.assertAllCloseAccordingToType([3.0, 4.0], self.evaluate(var1))
59 self.evaluate(var1))
67 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
71 zip([grads0, grads1], [var0, var1]))
76 resources.initialize_resources([var0, var1]).run()
79 self.assertAllCloseAccordingToType([3.0, 4.0], self.evaluate(var1))
86 self.evaluate(var1))
93 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
[all …]
Dftrl_test.py46 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0],
50 var1 = 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])
87 var1 = variables.Variable([4.0, 3.0], 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])
139 var1 = variables.Variable([4.0, 3.0], dtype=dtype)
[all …]
Dproximal_adagrad_test.py41 var1 = 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])
65 self.assertStartsWith(opt_vars[1].name, var1._shared_name)
78 var1 = variables.Variable([4.0, 3.0])
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])
124 var1 = variables.Variable([4.0, 3.0])
[all …]
Dmomentum_test.py53 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0],
58 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
68 mom_update = mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
74 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
80 slot1 = mom_opt.get_slot(var1, "momentum")
81 self.assertEqual(slot1.get_shape(), var1.get_shape())
100 self.evaluate(var1))
103 mom_opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
123 ]), self.evaluate(var1))
143 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0],
[all …]
Dproximal_gradient_descent_test.py42 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0])
45 var1 = 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])
74 var1 = variables.Variable([4.0, 3.0])
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])
117 var1 = variables.Variable([4.0, 3.0])
[all …]
Dadagrad_da_test.py43 var1 = resource_variable_ops.ResourceVariable([0.0, 0.0], dtype=dtype)
46 var1 = 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])
111 var1 = variables.Variable([4.0, 3.0], dtype=dtype)
122 zip([grads0, grads1], [var0, var1]), global_step=global_step)
125 v0_val, v1_val = self.evaluate([var0, var1])
132 v0_val, v1_val = self.evaluate([var0, var1])
143 var1 = variables.Variable([4.0, 3.0], dtype=dtype)
[all …]
Drmsprop_test.py106 var1 = resource_variable_ops.ResourceVariable(var1_np)
109 var1 = variables.Variable(var1_np)
119 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
124 mg1 = opt.get_slot(var1, "mg")
128 rms1 = opt.get_slot(var1, "rms")
132 mom1 = opt.get_slot(var1, "momentum")
144 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
166 self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
229 var1 = variables.Variable(var1_np)
244 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
[all …]
Dadagrad_test.py46 var1 = resource_variable_ops.ResourceVariable([3.0, 4.0], dtype=dtype)
49 var1 = variables.Variable([3.0, 4.0], 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])
125 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
131 zip([grads0, grads1], [var0, var1]))
135 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
145 self.evaluate(var1))
[all …]
/external/tensorflow/tensorflow/python/keras/optimizer_v2/
Dgradient_descent_test.py46 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
50 sgd_op = sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
58 self.evaluate(var1))
62 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
66 sgd_op = sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
72 sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
77 self.evaluate(var1))
82 sgd.apply_gradients(zip([grads0, grads1], [var0, var1]))
89 self.evaluate(var1))
120 var1 = variables.Variable([3.0, 4.0], dtype=dtype)
[all …]
Dftrl_test.py43 var1 = variables.Variable([0.0, 0.0], dtype=dtype)
46 var1 = 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])
82 var1 = variables.Variable([4.0, 3.0], 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])
134 var1 = variables.Variable([4.0, 3.0], dtype=dtype)
[all …]
Dadagrad_test.py81 var1 = variables.Variable(var1_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]))
115 self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
132 var1 = variables.Variable(var1_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]))
166 self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
[all …]
Drmsprop_test.py115 var1 = variables.Variable(var1_np, dtype=dtype)
125 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
130 mg1 = opt.get_slot(var1, "mg")
137 mom1 = opt.get_slot(var1, "momentum")
144 rms1 = opt.get_slot(var1, "rms")
156 self.assertAllClose([3.0, 4.0], self.evaluate(var1))
179 self.assertAllCloseAccordingToType(var1_np, self.evaluate(var1))
190 var1 = variables.Variable(var1_np)
207 update = opt.apply_gradients(zip([grads0, grads1], [var0, var1]))
212 rms1 = opt.get_slot(var1, "rms")
[all …]
/external/llvm-project/lld/test/ELF/
Daarch64-tlsld-ldst.s15 add x8, x8, :tprel_hi12:var1
16 ldr x0, [x8, :tprel_lo12_nc:var1]
52 .globl var1 symbol
57 .type var1,@object
67 .size var1, 16
69 var1: label
71 .size var1, 8
75 .size var1, 4
/external/deqp/external/vulkancts/data/vulkan/amber/spirv_assembly/instruction/spirv1p4/opptrequal/
Ddifferent_ssbos_equal.amber12 OpEntryPoint GLCompute %main "main" %var1 %var2 %var3 %out_var
17 OpDecorate %var1 DescriptorSet 0
18 OpDecorate %var1 Binding 0
35 %var1 = OpVariable %ptr_ssbo_struct StorageBuffer
43 %var1_rta_gep = OpAccessChain %ptr_ssbo_rta %var1 %int_0
44 %var1_int_gep = OpAccessChain %ptr_ssbo_int %var1 %int_0 %int_0
49 ; var1 vs var2
50 %v1_eq_v2 = OpPtrEqual %bool %var1 %var2
65 ; var1 vs var3
66 %v1_eq_v3 = OpPtrEqual %bool %var1 %var3
[all …]
/external/deqp/external/vulkancts/data/vulkan/amber/spirv_assembly/instruction/spirv1p4/opptrnotequal/
Ddifferent_ssbos_not_equal.amber12 OpEntryPoint GLCompute %main "main" %var1 %var2 %var3 %out_var
17 OpDecorate %var1 DescriptorSet 0
18 OpDecorate %var1 Binding 0
35 %var1 = OpVariable %ptr_ssbo_struct StorageBuffer
43 %var1_rta_gep = OpAccessChain %ptr_ssbo_rta %var1 %int_0
44 %var1_int_gep = OpAccessChain %ptr_ssbo_int %var1 %int_0 %int_0
49 ; var1 vs var2
50 %v1_neq_v2 = OpPtrNotEqual %bool %var1 %var2
65 ; var1 vs var3
66 %v1_neq_v3 = OpPtrNotEqual %bool %var1 %var3
[all …]

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