| /external/vulkan-validation-layers/libs/glm/detail/ |
| D | glm.cpp | 83 template struct tvec2<float32, lowp>;
94 template struct tvec2<float32, mediump>;
105 template struct tvec2<float32, highp>;
117 template struct tvec3<float32, lowp>;
128 template struct tvec3<float32, mediump>;
139 template struct tvec3<float32, highp>;
151 template struct tvec4<float32, lowp>;
162 template struct tvec4<float32, mediump>;
173 template struct tvec4<float32, highp>;
177 template struct tmat2x2<float32, lowp>;
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | nary_ops_test.py | 58 [np.array([[1, 2, 3]], dtype=np.float32)],
59 expected=np.array([[1, 2, 3]], dtype=np.float32))
62 [np.array([1, 2], dtype=np.float32),
63 np.array([10, 20], dtype=np.float32)],
64 expected=np.array([11, 22], dtype=np.float32))
66 [np.array([-4], dtype=np.float32),
67 np.array([10], dtype=np.float32),
68 np.array([42], dtype=np.float32)],
69 expected=np.array([48], dtype=np.float32))
94 [np.array([[1, 2, 3]], dtype=np.float32)],
[all …]
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| D | ternary_ops_test.py | 45 np.float32(1),
46 np.float32(2),
48 expected=np.array([1], dtype=np.float32))
51 np.float32(1),
52 np.float32(4),
54 expected=np.array([1, 2.5, 4], dtype=np.float32))
74 np.array(2, dtype=np.float32),
75 np.array(7, dtype=np.float32),
76 expected=np.array(7, dtype=np.float32))
81 np.array([1, 2, 3, 4], dtype=np.float32),
[all …]
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| D | fused_batchnorm_test.py | 70 x_val = np.random.random_sample(x_shape).astype(np.float32)
71 scale_val = np.random.random_sample(scale_shape).astype(np.float32)
73 offset_val = np.random.random_sample(scale_shape).astype(np.float32)
77 t_val = array_ops.placeholder(np.float32, shape=x_shape, name="x")
78 scale = array_ops.placeholder(np.float32, shape=scale_shape, name="scale")
80 np.float32, shape=scale_shape, name="offset")
105 x_val = np.random.random_sample(x_shape).astype(np.float32)
106 scale_val = np.random.random_sample(scale_shape).astype(np.float32)
108 offset_val = np.random.random_sample(scale_shape).astype(np.float32)
109 mean_val = np.random.random_sample(scale_shape).astype(np.float32)
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| D | stack_ops_test.py | 36 v = array_ops.placeholder(dtypes.float32)
37 h = gen_data_flow_ops._stack_v2(size, dtypes.float32, stack_name="foo")
40 c1 = gen_data_flow_ops._stack_pop_v2(h, dtypes.float32)
46 x = array_ops.placeholder(dtypes.float32)
47 h = gen_data_flow_ops._stack_v2(5, dtypes.float32, stack_name="foo")
50 c1 = gen_data_flow_ops._stack_pop_v2(h, dtypes.float32)
55 v = array_ops.placeholder(dtypes.float32)
56 h1 = gen_data_flow_ops._stack_v2(5, dtypes.float32, stack_name="foo")
59 c1 = gen_data_flow_ops._stack_pop_v2(h1, dtypes.float32)
60 h2 = gen_data_flow_ops._stack_v2(5, dtypes.float32, stack_name="bar")
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| D | function_test.py | 41 aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
42 bval = np.array([5, 6, 7, 8]).reshape([2, 2]).astype(np.float32)
47 @function.Defun(dtypes.float32, dtypes.float32)
67 aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
68 bval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
73 @function.Defun(dtypes.float32, dtypes.float32)
91 aval = np.array([4, 3, 2, 1]).reshape([2, 2]).astype(np.float32)
92 bval = np.array([5, 6, 7, 8]).reshape([2, 2]).astype(np.float32)
97 @function.Defun(dtypes.float32, dtypes.float32)
111 @function.Defun(dtypes.float32, noinline=True)
[all …]
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| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| D | conditioning_utils_test.py | 34 array_ops.placeholder(dtypes.float32, tensor_shape),
35 array_ops.placeholder(dtypes.float32, conditioning_shape))
40 array_ops.placeholder(dtypes.float32, (4, 1)),
41 array_ops.placeholder(dtypes.float32, (5, 1)))
45 array_ops.placeholder(dtypes.float32, (5, None)),
46 array_ops.placeholder(dtypes.float32, (5, 1)))
50 array_ops.placeholder(dtypes.float32, (5, 2)),
51 array_ops.placeholder(dtypes.float32, (5)))
55 array_ops.placeholder(dtypes.float32, (5, 4, 1)),
56 array_ops.placeholder(dtypes.float32, (5, 10)))
[all …]
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | vector_diffeomixture_test.py | 46 np.float32([2.]*dims),
51 multiplier=np.float32(1.1),
54 diag=np.linspace(2.5, 3.5, dims, dtype=np.float32),
75 np.float32([2.]*dims),
80 multiplier=np.float32(1.1),
83 diag=np.linspace(2.5, 3.5, dims, dtype=np.float32),
104 np.float32([2.]*dims),
109 multiplier=[np.float32(1.1)],
113 np.linspace(2.5, 3.5, dims, dtype=np.float32),
114 np.linspace(2.75, 3.25, dims, dtype=np.float32),
[all …]
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| D | vector_student_t_test.py | 80 df = np.asarray(3., dtype=np.float32)
82 loc = np.asarray([1], dtype=np.float32)
83 scale_diag = np.asarray([2.], dtype=np.float32)
91 x = 2. * self._rng.rand(4, 1).astype(np.float32) - 1.
102 df = np.asarray([1., 2, 3], dtype=np.float32)
107 dtype=np.float32)
111 dtype=np.float32)
114 x = 2. * self._rng.rand(4, 3, 3).astype(np.float32) - 1.
131 df = np.asarray([1., 2, 3], dtype=np.float32)
136 dtype=np.float32)
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | sparse_matmul_op_test.py | 37 64) / 128.0).reshape([rows, cols]).astype(np.float32)
49 x_dtype=dtypes.float32,
50 y_dtype=dtypes.float32):
62 np_x = math_ops.cast(tf_x, dtypes.float32).eval()
63 np_y = math_ops.cast(tf_y, dtypes.float32).eval()
75 x = np.arange(0., 4.).reshape([4, 1]).astype(np.float32)
76 y = np.arange(-1., 1.).reshape([1, 2]).astype(np.float32)
77 for x_dtype in (dtypes.float32, dtypes.bfloat16):
78 for y_dtype in (dtypes.float32, dtypes.bfloat16):
82 x = np.ones((4, 0)).astype(np.float32)
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| D | sparse_conditional_accumulator_test.py | 62 dtypes_lib.float32, name="Q")
75 dtypes_lib.float32,
94 dtypes_lib.float32, name="Q")
100 dtypes_lib.float32, name="Q", shape=tensor_shape.TensorShape([1]))
107 dtypes_lib.float32, name="Q", shape=tensor_shape.TensorShape([3, 3]))
111 values=np.array([[0, 0, 1], [3, 0, 4]]).astype(np.float32)))
117 dtypes = [dtypes_lib.float16, dtypes_lib.float32, dtypes_lib.float64]
140 dtypes_lib.float32, name="Q", shape=tensor_shape.TensorShape([2, 2]))
142 dtypes_lib.float32, name="Q", shape=tensor_shape.TensorShape([2, 2]))
170 dtypes_lib.float32, name="Q", shape=())
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| D | stack_ops_test.py | 38 -1, elem_type=dtypes.float32, stack_name="foo")
41 c1 = gen_data_flow_ops._stack_pop_v2(h, dtypes.float32)
51 x = constant_op.constant(a, dtype=dtypes.float32)
53 -1, elem_type=dtypes.float32, stack_name="foo")
56 c1 = gen_data_flow_ops._stack_pop_v2(h, dtypes.float32)
67 -1, elem_type=dtypes.float32, stack_name="foo")
74 a = constant_op.constant(np.ones(2000), dtype=dtypes.float32)
81 v = constant_op.constant(np.zeros(2000), dtype=dtypes.float32)
89 ny = y + gen_data_flow_ops._stack_pop_v2(h, dtypes.float32)
103 -1, elem_type=dtypes.float32, stack_name="foo")
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| D | variable_ops_test.py | 35 np.float32: dtypes.float32,
52 for dtype in [np.float32, np.float64, np.int32, np.int64]:
66 p = state_ops.variable_op([1, 2], dtypes.float32)
68 p = state_ops.variable_op([1, 2], dtypes.float32, set_shape=False)
73 var = state_ops.variable_op(value.shape, dtypes.float32)
80 var = state_ops.variable_op(value.shape, dtypes.float32)
87 var = state_ops.variable_op(value.shape, dtypes.float32, set_shape=False)
94 var = state_ops.variable_op(value.shape, dtypes.float32, set_shape=False)
100 tensor = array_ops.placeholder(dtypes.float32)
107 var = state_ops.variable_op(shape, dtypes.float32)
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| D | parse_single_example_op_test.py | 131 c_default = np.random.rand(2).astype(np.float32)
158 (2,), dtypes.float32, default_value=c_default),
177 (2,), dtype=dtypes.float32),
210 "a": parsing_ops.FixedLenFeature((1, 3), dtypes.float32)
227 "a": parsing_ops.FixedLenFeature(None, dtypes.float32)
251 np.array([3.0, 4.0], dtype=np.float32),
256 "st_c": empty_sparse(np.float32),
259 "st_c": empty_sparse(np.float32),
263 np.array([1.0, 2.0, -1.0], dtype=np.float32),
273 "st_c": parsing_ops.VarLenFeature(dtypes.float32),
[all …]
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| D | cast_op_test.py | 39 if dtype == np.float32:
40 return dtypes.float32
71 np.float32, np.float64, np.int64, np.complex64, np.complex128
75 np.float32, np.float64, np.int32, np.int64, np.complex64,
82 self._test(x.astype(np.bool), np.float32, use_gpu)
83 self._test(x.astype(np.uint8), np.float32, use_gpu)
90 if x.dtype == np.float32 or x.dtype == np.float64:
98 f4 = np.finfo(np.float32)
107 a = np.random.uniform(-100, 100, 100).astype(np.float32)
109 b = math_ops.cast(math_ops.cast(a, dtypes.bfloat16), dtypes.float32)
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| D | list_ops_test.py | 45 l = list_ops.empty_tensor_list(element_dtype=dtypes.float32,
48 l, e = list_ops.tensor_list_pop_back(l, element_dtype=dtypes.float32)
58 l = list_ops.empty_tensor_list(element_dtype=dtypes.float32,
62 t = list_ops.tensor_list_stack(l, element_dtype=dtypes.float32)
74 l, e = list_ops.tensor_list_pop_back(l, element_dtype=dtypes.float32)
76 l, e = list_ops.tensor_list_pop_back(l, element_dtype=dtypes.float32)
89 e0 = list_ops.tensor_list_get_item(l, 0, element_dtype=dtypes.float32)
92 t = list_ops.tensor_list_stack(l, element_dtype=dtypes.float32)
102 l = list_ops.empty_tensor_list(element_dtype=dtypes.float32,
106 _, e = list_ops.tensor_list_pop_back(l, element_dtype=dtypes.float32)
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| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_fused_batchnorm_test.py | 166 x32_init_val = x_init_val.astype(np.float32)
218 x32 = constant_op.constant(x_val, name='x32', dtype=dtypes.float32)
304 x32 = constant_op.constant(x_val, dtype=dtypes.float32, name='x32')
306 grad_y_val, dtype=dtypes.float32, name='grad_y32')
343 for dtype in [np.float16, np.float32]:
346 x_shape, dtype, [1], np.float32, use_gpu=True, data_format='NHWC')
348 x_shape, dtype, [1], np.float32, use_gpu=True, data_format='NCHW')
350 x_shape, dtype, [1], np.float32, use_gpu=False, data_format='NHWC')
355 for dtype in [np.float16, np.float32]:
357 x_shape, dtype, [2], np.float32, use_gpu=True, data_format='NHWC')
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| /external/tensorflow/tensorflow/python/estimator/canned/ |
| D | parsing_utils_test.py | 35 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
46 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
59 parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
72 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
74 'c': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
84 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
86 'c': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
121 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
122 'b': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
132 'a': parsing_ops.FixedLenFeature((1,), dtype=dtypes.float32),
[all …]
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| /external/tensorflow/tensorflow/python/framework/ |
| D | function_test.py | 79 @function.Defun(dtypes.float32, func_name="MyIdentity")
91 @function.Defun(dtypes.float32, func_name="MyIdentity")
107 dtypes.float32, func_name="MyIdentity", out_names=["my_result_name"])
120 dtypes.float32, func_name="MyIdentity",
134 @function.Defun(dtypes.float32, dtypes.float32, func_name="APlus2B")
146 @function.Defun(dtypes.float32, dtypes.float32)
158 dtypes.float32,
159 dtypes.float32,
173 @function.Defun(dtypes.float32, func_name="Duplicate")
190 @function.Defun(dtypes.float32, func_name="XSquarePlusOneFn")
[all …]
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| /external/tensorflow/tensorflow/contrib/tpu/python/tpu/ |
| D | tpu_infeed_test.py | 39 tuple_types=[dtypes.float32, dtypes.int32, dtypes.int32])
42 [dtypes.float32, dtypes.int32, dtypes.int32])
60 number_of_tuple_elements=2, tuple_types=[dtypes.float32])
71 i.set_tuple_types([dtypes.float32, dtypes.int32])
72 self.assertEqual(i.tuple_types, [dtypes.float32, dtypes.int32])
73 i.set_tuple_types([dtypes.float32, dtypes.float32])
74 self.assertEqual(i.tuple_types, [dtypes.float32, dtypes.float32])
76 i.set_tuple_types([dtypes.float32])
88 t2 = constant_op.constant(2.0, dtypes.float32, shape=[3, 18])
91 self.assertEqual(i.tuple_types, [dtypes.int32, dtypes.float32])
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| /external/tensorflow/tensorflow/tools/quantization/ |
| D | quantize_graph_test.py | 58 a_constant_name, value=a, dtype=dtypes.float32, shape=[m, k])
61 b_constant_name, value=b, dtype=dtypes.float32, shape=[k, n])
65 quantize_graph.set_attr_dtype(mat_mul_node, "T", dtypes.float32)
84 dtype=dtypes.float32,
90 dtype=dtypes.float32,
95 quantize_graph.set_attr_dtype(conv_node, "T", dtypes.float32)
203 shape_constant_name, value=-0.8, dtype=dtypes.float32, shape=[1])
238 quantize_graph.set_attr_dtype(n, "T", dtypes.float32)
245 "input", value=[0, 1, 2, 3], dtype=dtypes.float32, shape=[4, 1])
249 dtype=dtypes.float32,
[all …]
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| /external/tensorflow/tensorflow/python/tools/ |
| D | optimize_for_inference_test.py | 82 unused_constant_name, value=0, dtype=dtypes.float32, shape=[])
87 self.set_attr_dtype(unconnected_add_node, "T", dtypes.float32)
90 a_constant_name, value=1, dtype=dtypes.float32, shape=[])
99 b_constant_name, value=1, dtype=dtypes.float32, shape=[])
109 self.set_attr_dtype(add_node, "T", dtypes.float32)
113 self.set_attr_dtype(unused_output_add_node, "T", dtypes.float32)
118 a_constant_name, value=1, dtype=dtypes.float32, shape=[])
121 b_constant_name, value=1, dtype=dtypes.float32, shape=[])
125 self.set_attr_dtype(add_node, "T", dtypes.float32)
129 graph_def, [], [add_name], dtypes.float32.as_datatype_enum)
[all …]
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| /external/tensorflow/tensorflow/contrib/fused_conv/python/ops/ |
| D | fused_conv2d_bias_activation_op_test.py | 160 return [dtypes.float32]
239 x1 = np.random.rand(*tensor_in_sizes).astype(np.float32)
240 x2 = np.random.rand(*filter_in_sizes).astype(np.float32)
241 x3 = np.random.rand(*[filter_in_sizes[-1]]).astype(np.float32)
454 array_ops.placeholder(dtypes.float32),
455 array_ops.placeholder(dtypes.float32),
456 array_ops.placeholder(dtypes.float32),
465 array_ops.placeholder(dtypes.float32, shape=[1, 3]),
466 array_ops.placeholder(dtypes.float32),
467 array_ops.placeholder(dtypes.float32),
[all …]
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| /external/tensorflow/tensorflow/contrib/lite/testing/ |
| D | generate_examples.py | 231 tf.float32: (np.float32, "FLOAT"),
245 if dtype in (tf.float32, tf.float16):
275 dtype=tf.float32, name="input", shape=parameters["input_shape"])
276 filter_value = tf.zeros((3, 3, TEST_INPUT_DEPTH, 8), tf.float32)
284 input_values = create_tensor_data(tf.float32, parameters["input_shape"])
528 dtype=tf.float32, name="input", shape=parameters["input_shape"])
538 input_values = create_tensor_data(tf.float32, parameters["input_shape"])
557 dtype=tf.float32, name="input", shape=parameters["input_shape"])
563 np.float32, parameters["input_shape"], min_value=-4, max_value=10)
581 dtype=tf.float32, name="input", shape=parameters["input_shape"])
[all …]
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| /external/tensorflow/tensorflow/python/client/ |
| D | session_partial_run_test.py | 45 a = array_ops.placeholder(dtypes.float32, shape=[])
46 b = array_ops.placeholder(dtypes.float32, shape=[])
47 c = array_ops.placeholder(dtypes.float32, shape=[])
67 a = array_ops.placeholder(dtypes.float32, shape=[])
68 b = array_ops.placeholder(dtypes.float32, shape=[])
69 c = array_ops.placeholder(dtypes.float32, shape=[])
78 a = array_ops.placeholder(dtypes.float32, shape=[])
79 b = array_ops.placeholder(dtypes.float32, shape=[])
80 c = array_ops.placeholder(dtypes.float32, shape=[])
98 a = constant_op.constant(2.0, dtypes.float32)
[all …]
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