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/external/vulkan-validation-layers/layers/generated/
Dvk_enum_string_helper.h42 …ic inline const char* string_VkPipelineCacheHeaderVersion(VkPipelineCacheHeaderVersion input_value) in string_VkPipelineCacheHeaderVersion() argument
44 switch ((VkPipelineCacheHeaderVersion)input_value) in string_VkPipelineCacheHeaderVersion()
53 static inline const char* string_VkResult(VkResult input_value) in string_VkResult() argument
55 switch ((VkResult)input_value) in string_VkResult()
126 static inline const char* string_VkStructureType(VkStructureType input_value) in string_VkStructureType() argument
128 switch ((VkStructureType)input_value) in string_VkStructureType()
881 static inline const char* string_VkSystemAllocationScope(VkSystemAllocationScope input_value) in string_VkSystemAllocationScope() argument
883 switch ((VkSystemAllocationScope)input_value) in string_VkSystemAllocationScope()
900 static inline const char* string_VkInternalAllocationType(VkInternalAllocationType input_value) in string_VkInternalAllocationType() argument
902 switch ((VkInternalAllocationType)input_value) in string_VkInternalAllocationType()
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/external/tensorflow/tensorflow/compiler/mlir/tosa/transforms/
Dlegalize_common.h43 Value input_value,
82 Value input_value,
89 Value input_value,
96 Value input_value, Value dim_value);
100 Value result_value, Value input_value,
120 Value input_value,
127 Value input_value,
134 Value input_value, int32_t num_split, int32_t axis);
139 Value input_value, SmallVectorImpl<int32_t>& size_split, int32_t axis);
144 Value input_value, Value begin_value, Value end_value, Value strides_value,
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/external/tensorflow/tensorflow/lite/testing/op_tests/
Dtopk.py35 input_value = tf.compat.v1.placeholder(
41 inputs = [input_value, k]
44 inputs = [input_value]
45 out = tf.nn.top_k(input_value, k)
49 input_value = create_tensor_data(parameters["input_dtype"],
53 return [input_value, k], sess.run(
54 outputs, feed_dict=dict(zip(inputs, [input_value, k])))
56 return [input_value], sess.run(
57 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dfloor.py33 input_value = tf.compat.v1.placeholder(
37 out = tf.floor(input_value)
38 return [input_value], [out]
41 input_value = create_tensor_data(parameters["input_dtype"],
43 return [input_value], sess.run(outputs, feed_dict={inputs[0]: input_value})
Dceil.py33 input_value = tf.compat.v1.placeholder(
37 out = tf.math.ceil(input_value)
38 return [input_value], [out]
41 input_value = create_tensor_data(parameters["input_dtype"],
43 return [input_value], sess.run(outputs, feed_dict={inputs[0]: input_value})
Drank.py33 input_value = tf.compat.v1.placeholder(
35 out = tf.rank(input_value)
36 return [input_value], [out]
39 input_value = create_tensor_data(parameters["input_dtype"],
41 return [input_value], sess.run(
42 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dround.py33 input_value = tf.compat.v1.placeholder(
37 out = tf.round(input_value)
38 return [input_value], [out]
41 input_value = create_tensor_data(parameters["input_dtype"],
43 return [input_value], sess.run(outputs, feed_dict={inputs[0]: input_value})
Droll.py61 input_value = tf.compat.v1.placeholder(
66 input_value, shift=parameters["shift"], axis=parameters["axis"])
67 return [input_value], [outs]
70 input_value = create_tensor_data(parameters["input_dtype"],
72 return [input_value], sess.run(
73 outputs, feed_dict=dict(zip(inputs, [input_value])))
118 input_value = create_tensor_data(
122 return [input_value, shift_value, axis_value], sess.run(
124 feed_dict=dict(zip(inputs, [input_value, shift_value, axis_value])))
Darg_min_max.py58 input_value = tf.compat.v1.placeholder(
68 input_value, axis, output_type=parameters["output_type"])
71 input_value, axis, output_type=parameters["output_type"])
72 return [input_value], [out]
75 input_value = create_tensor_data(parameters["input_dtype"],
77 return [input_value], sess.run(
78 outputs, feed_dict=dict(zip(inputs, [input_value])))
Drfft2d.py37 input_value = tf.compat.v1.placeholder(
41 outs = tf.signal.rfft2d(input_value, fft_length=parameters["fft_length"])
42 return [input_value], [outs]
45 input_value = create_tensor_data(parameters["input_dtype"],
47 return [input_value], sess.run(
48 outputs, feed_dict=dict(zip(inputs, [input_value])))
Drfft.py34 input_value = tf.compat.v1.placeholder(
38 outs = tf.signal.rfft(input_value, fft_length=parameters["fft_length"])
39 return [input_value], [outs]
42 input_value = create_tensor_data(parameters["input_dtype"],
44 return [input_value], sess.run(
45 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dstft.py36 input_value = tf.compat.v1.placeholder(
41 input_value,
45 return [input_value], [outs]
48 input_value = create_tensor_data(parameters["input_dtype"],
50 return [input_value], sess.run(
51 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dreverse_sequence.py48 input_value = tf.compat.v1.placeholder(
53 input_value,
57 return [input_value], [outs]
60 input_value = create_tensor_data(parameters["input_dtype"],
62 return [input_value], sess.run(
63 outputs, feed_dict=dict(zip(inputs, [input_value])))
Drandom_standard_normal.py49 input_value = tf.compat.v1.placeholder(
54 shape=input_value, dtype=parameters["dtype"], seed=parameters["seed2"])
55 return [input_value], [out]
58 input_value = create_tensor_data(
63 return [input_value], sess.run(
64 outputs, feed_dict=dict(zip(inputs, [input_value])))
Drandom_uniform.py49 input_value = tf.compat.v1.placeholder(
54 shape=input_value, dtype=parameters["dtype"], seed=parameters["seed2"])
55 return [input_value], [out]
58 input_value = create_tensor_data(
63 return [input_value], sess.run(
64 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dshape.py41 input_value = tf.compat.v1.placeholder(
48 reshaped = tf.reshape(input_value, shape=new_shape)
50 return [input_value, new_shape], [out]
53 input_value = create_tensor_data(parameters["input_dtype"],
56 return [input_value, new_shape], sess.run(
57 outputs, feed_dict=dict(zip(inputs, [input_value, new_shape])))
Dcast.py73 input_value = tf.compat.v1.placeholder(
77 out = tf.cast(input_value, parameters["output_dtype"])
78 return [input_value], [out]
81 input_value = create_tensor_data(parameters["input_dtype"],
83 return [input_value], sess.run(
84 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dtile.py52 input_value = tf.compat.v1.placeholder(
60 out = tf.tile(input_value, multiplier_value)
61 return [input_value, multiplier_value], [out]
65 input_value = create_tensor_data(
74 return [input_value, multipliers_value], sess.run(
77 inputs[0]: input_value,
/external/icing/icing/util/
Dmath-util.h41 static IntType RoundDownTo(IntType input_value, IntType rounding_value) { in RoundDownTo() argument
45 if (input_value <= 0) { in RoundDownTo()
53 return (input_value / rounding_value) * rounding_value; in RoundDownTo()
62 static IntType RoundUpTo(IntType input_value, IntType rounding_value) { in RoundUpTo() argument
66 if (input_value <= 0) { in RoundUpTo()
74 const IntType remainder = input_value % rounding_value; in RoundUpTo()
75 return (remainder == 0) ? input_value in RoundUpTo()
76 : (input_value - remainder + rounding_value); in RoundUpTo()
/external/XNNPACK/src/subgraph/
Dvalidation.c53 const struct xnn_value* input_value) in xnn_subgraph_check_input_type_dense() argument
55 if (input_value->type != xnn_value_type_dense_tensor) { in xnn_subgraph_check_input_type_dense()
58 xnn_node_type_to_string(node_type), input_id, input_value->type); in xnn_subgraph_check_input_type_dense()
67 const struct xnn_value* input_value, in xnn_subgraph_check_nth_input_type_dense() argument
70 if (input_value->type != xnn_value_type_dense_tensor) { in xnn_subgraph_check_nth_input_type_dense()
73 xnn_node_type_to_string(node_type), nth, input_id, input_value->type); in xnn_subgraph_check_nth_input_type_dense()
107 const struct xnn_value* input_value, in xnn_subgraph_check_datatype_matches() argument
111 assert(input_value->datatype != xnn_datatype_invalid); in xnn_subgraph_check_datatype_matches()
113 if (input_value->datatype != output_value->datatype) { in xnn_subgraph_check_datatype_matches()
118 xnn_datatype_to_string(input_value->datatype), in xnn_subgraph_check_datatype_matches()
/external/tensorflow/tensorflow/lite/experimental/mlir/testing/op_tests/
Droll.py65 input_value = tf.compat.v1.placeholder(
70 input_value, shift=parameters["shift"], axis=parameters["axis"])
71 return [input_value], [outs]
74 input_value = create_tensor_data(parameters["input_dtype"],
76 return [input_value], sess.run(
77 outputs, feed_dict=dict(zip(inputs, [input_value])))
122 input_value = create_tensor_data(
126 return [input_value, shift_value, axis_value], sess.run(
128 feed_dict=dict(zip(inputs, [input_value, shift_value, axis_value])))
Drfft.py38 input_value = tf.compat.v1.placeholder(
42 outs = tf.signal.rfft(input_value, fft_length=parameters["fft_length"])
43 return [input_value], [outs]
46 input_value = create_tensor_data(parameters["input_dtype"],
48 return [input_value], sess.run(
49 outputs, feed_dict=dict(zip(inputs, [input_value])))
Drfft2d.py41 input_value = tf.compat.v1.placeholder(
45 outs = tf.signal.rfft2d(input_value, fft_length=parameters["fft_length"])
46 return [input_value], [outs]
49 input_value = create_tensor_data(parameters["input_dtype"],
51 return [input_value], sess.run(
52 outputs, feed_dict=dict(zip(inputs, [input_value])))
Dstft.py40 input_value = tf.compat.v1.placeholder(
45 input_value,
49 return [input_value], [outs]
52 input_value = create_tensor_data(parameters["input_dtype"],
54 return [input_value], sess.run(
55 outputs, feed_dict=dict(zip(inputs, [input_value])))
/external/tensorflow/tensorflow/lite/kernels/internal/reference/
Dprelu.h49 const int32_t input_value = in BroadcastPrelu4DSlow() local
52 if (input_value >= 0) { in BroadcastPrelu4DSlow()
54 input_value, params.output_multiplier_1, params.output_shift_1); in BroadcastPrelu4DSlow()
61 input_value * alpha_value, params.output_multiplier_2, in BroadcastPrelu4DSlow()
88 const int32_t input_value = params.input_offset + input_data[i]; in Prelu() local
90 if (input_value >= 0) { in Prelu()
92 input_value, params.output_multiplier_1, params.output_shift_1); in Prelu()
96 output_value = MultiplyByQuantizedMultiplier(input_value * alpha_value, in Prelu()

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