| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/ |
| D | merge_control_flow.mlir | 1 // RUN: tf-opt %s -tf-merge-control-flow | FileCheck %s
8 // CHECK: "tf.IfRegion"
9 // CHECK: "tf.IfRegion"
11 %0 = "tf.Const"() {value = dense<true> : tensor<i1>} : () -> tensor<i1>
12 %1 = "tf.Const"() {value = dense<false> : tensor<i1>} : () -> tensor<i1>
13 "tf.IfRegion"(%0) ( {
14 %2 = "tf.A"() : () -> (tensor<f32>)
15 "tf.Yield"() : () -> ()
17 "tf.Yield"() : () -> ()
19 "tf.IfRegion"(%1) ( {
[all …]
|
| D | stack_ops_decomposition.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-stack-ops-decomposition | FileCheck %s
7 // CHECK-NEXT: "tf.Const"() {value = dense<10> : tensor<i32>}
8 %max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
9 …// CHECK-NEXT: %[[ZERO_SCALAR:.*]] = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<…
10 // CHECK-NEXT: %[[CAST_ZERO:.*]] = "tf.Cast"(%[[ZERO_SCALAR]]) : (tensor<i32>) -> tensor<f32>
11 …// CHECK-NEXT: %[[CONST10:.*]] = "tf.Const"() {value = dense<10> : tensor<1xi32>} : () -> tensor<1…
12 …// CHECK-NEXT: %[[BROADCAST:.*]] = "tf.BroadcastTo"(%[[CAST_ZERO]], %[[CONST10]]) : (tensor<f32>, …
13 // CHECK-NEXT: %[[BUFFER:.*]] = "tf.MlirLocalVarOp"() : () -> tensor<!tf.resource<tensor<10xf32>>>
14 // CHECK-NEXT: %[[SIZE:.*]] = "tf.MlirLocalVarOp"() : () -> tensor<!tf.resource<tensor<1xi32>>>
15 …// CHECK-NEXT: %[[ZERO:.*]] = "tf.Const"() {value = dense<0> : tensor<1xi32>} : () -> tensor<1xi32>
[all …]
|
| D | tpu_reorder_replicate_and_partitioned_inputs.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-tpu-reorder-replicate-partitioned-input…
4 …tf.resource<tensor<10x3xf32>>>, [[ARG1:%.*]]: tensor<!tf.resource<tensor<10x3xf32>>>, [[ARG2:%.*]]…
5 …tf.resource<tensor<10x3xf32>>>, %arg1: tensor<!tf.resource<tensor<10x3xf32>>>, %arg2: tensor<!tf.r…
6 // CHECK: [[RI_0:%.*]] = "tf.TPUReplicatedInput"([[ARG0]], [[ARG2]])
7 // CHECK: [[RI_1:%.*]] = "tf.TPUReplicatedInput"([[ARG1]], [[ARG3]])
8 // CHECK: [[PI:%.*]] = "tf.TPUPartitionedInput"([[RI_0]], [[RI_1]])
9 …tf.TPUPartitionedInput"(%arg0, %arg1) {_XlaSharding = "", partition_dim = -1 : i64} : (tensor<!tf.…
10 …tf.TPUPartitionedInput"(%arg2, %arg3) {_XlaSharding = "", partition_dim = -1 : i64} : (tensor<!tf.…
11 …%ri = "tf.TPUReplicatedInput"(%pi_0, %pi_1) : (tensor<!tf.resource<tensor<10x3xf32>>>, tensor<!tf.…
13 return %ri : tensor<!tf.resource<tensor<10x3xf32>>>
[all …]
|
| D | tensor_array_ops_decomposition.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-tensor-array-ops-decomposition | FileCh…
7 %size = "tf.Const"() {value = dense<5> : tensor<i32>} : () -> tensor<i32>
8 // CHECK: %[[BUFFER:.*]] = "tf.BroadcastTo"(%2, %3)
10 // CHECK: %[[VAR:.*]] = "tf.MlirLocalVarOp"() : () -> tensor<!tf.resource<tensor<5x3xf32>>>
11 // CHECK: "tf.AssignVariableOp"(%[[VAR]], %[[BUFFER]])
12 …tf.TensorArrayV3"(%size) {dtype = f32, element_shape = #tf.shape<3>, dynamic_size = false, clear_a…
13 // CHECK: %[[IND:.*]] = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
14 %index = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
15 …// CHECK: %[[VAL:.*]] = "tf.Const"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00]> : …
16 %value = "tf.Const"() {value = dense<[1.0, 2.0, 3.0]> : tensor<3xf32>} : () -> tensor<3xf32>
[all …]
|
| D | mark_ops_for_outside_compilation.mlir | 1 // RUN: tf-opt %s -tf-mark-ops-for-outside-compilation | FILECHECK_OPTS="" FileCheck %s
6 // CHECK: "tf.UnsupportedOp"
8 // CHECK: "tf.Identity"
10 %1 = "tf.UnsupportedOp"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
11 %2 = "tf.Identity"(%1) : (tensor<i32>) -> tensor<i32>
20 // CHECK: "tf.UnsupportedOp"
22 // CHECK: "tf.Identity"
24 %1 = "tf.UnsupportedOp"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
25 %2 = "tf.Identity"(%1) : (tensor<i32>) -> tensor<i32>
32 func @assert_op_string_operand(%arg0: tensor<!tf.string>) -> tensor<i32> {
[all …]
|
| D | decompose_resource_ops.mlir | 1 // RUN: tf-opt %s -split-input-file -tf-device-decompose-resource-ops | FileCheck %s
8 …%0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf.resource<tensor<…
10 // CHECK: %[[ONE:[0-9]*]] = "tf.Const"() {value = dense<1> : tensor<i32>}
11 // CHECK: %[[RES_READ_VAL:[0-9]*]] = "tf.ReadVariableOp"
12 // CHECK-SAME: (tensor<*x!tf.resource<tensor<2x8xi32>>>) -> tensor<2x8xi32>
13 // CHECK: "tf.AddV2"(%[[RES_READ_VAL]], %[[ONE]])
15 // CHECK: "tf.AssignVariableOp"
17 %1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
18 …"tf.AssignAddVariableOp"(%0, %1) {dtype = "tfdtype$DT_INT32"} : (tensor<*x!tf.resource<tensor<2x8x…
25 // Tests that composite tf.AssignAddVariableOp operation is decomposed and
[all …]
|
| D | tensor_list_ops_decomposition.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-tensor-list-ops-decomposition | FileChe…
7 // CHECK-NEXT: "tf.Const"() {value = dense<> : tensor<0xi32>}
8 %elem_shape = "tf.Const"() {value = dense<> : tensor<0xi32>} : () -> tensor<0xi32>
9 // CHECK-NEXT: "tf.Const"() {value = dense<10> : tensor<i32>}
10 %max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
11 …// CHECK-NEXT: %[[ZERO_SCALAR:.*]] = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<…
12 // CHECK-NEXT: %[[CAST_ZERO:.*]] = "tf.Cast"(%[[ZERO_SCALAR]]) : (tensor<i32>) -> tensor<f32>
13 …// CHECK-NEXT: %[[CONST10:.*]] = "tf.Const"() {value = dense<10> : tensor<1xi32>} : () -> tensor<1…
14 …// CHECK-NEXT: %[[BROADCAST:.*]] = "tf.BroadcastTo"(%[[CAST_ZERO]], %[[CONST10]]) : (tensor<f32>, …
15 …// CHECK-NEXT: %[[ZERO:.*]] = "tf.Const"() {value = dense<0> : tensor<1xi32>} : () -> tensor<1xi32>
[all …]
|
| D | tpu_extract_outside_compilation.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-tpu-extract-outside-compilation | FILEC…
5 module attributes {tf.versions = {producer = 888 : i32}, tf.devices = ["/job:worker/replica:0/task:…
11 %1 = "tf.A"() : () -> tensor<?xi32>
12 %2 = "tf.B"(%1) : (tensor<?xi32>) -> tensor<?xi32>
26 // CHECK-NEXT: "tf.B"
31 // CHECK-NEXT: "tf.A"
34 "tf.A"() : () -> ()
35 "tf.B"() {_xla_outside_compilation = "cluster1"} : () -> ()
36 "tf.C"() : () -> ()
48 // CHECK-NEXT: "tf.B"
[all …]
|
| D | tpu_resource_partitioning.mlir | 1 // RUN: tf-opt %s -tf-tpu-resource-partition | FileCheck %s
6 // CHECK-SAME: ([[ARG0:%.+]]: tensor<!tf.resource<tensor<i32>>>, [[ARG1:%.+]]: tensor<!tf.resource<…
7 func @read_write_resource(%arg0: tensor<!tf.resource<tensor<i32>>>, %arg1: tensor<!tf.resource<tens…
8 // CHECK-DAG: [[READ0:%.+]] = "tf.ReadVariableOp"([[ARG0]])
9 // CHECK-DAG: [[READ1:%.+]] = "tf.ReadVariableOp"([[ARG1]])
10 // CHECK: [[INPUT:%.+]] = "tf.TPUPartitionedInput"([[READ0]], [[READ1]])
13 …tf.TPUPartitionedInput"(%arg0, %arg1) {N = 2 : i64, _XlaSharding = "", partition_dim = -1 : i64} :…
14 %1 = "tf.ReadVariableOp"(%0) : (tensor<!tf.resource<tensor<i32>>>) -> tensor<i32>
17 // CHECK: [[OUTPUT:%.+]]:2 = "tf.TPUPartitionedOutput"([[COMPUTATION]])
20 // CHECK-DAG: "tf.AssignVariableOp"([[ARG0]], [[OUTPUT]]#0)
[all …]
|
| D | tpu-dynamic-layout-pass.mlir | 1 // RUN: tf-opt %s -split-input-file -tf-tpu-dynamic-layout-pass | FileCheck %s
5 // CHECK: func @non_replicated(%[[ARG0:.*]]: tensor<*x!tf.resource> {tf.device = "/device:CPU:0"}) …
6 func @non_replicated(%arg0: tensor<*x!tf.resource> {tf.device = "/device:CPU:0"}) -> tensor<i32> {
8 // CHECK-NEXT: "tf._TPUCompileMlir"()
10 %1:2 = "tf._TPUCompileMlir"() {
14 mlir_module = "..."} : () -> (tensor<!tf.string>, tensor<2x!tf.string>)
15 tf_device.return %1#0, %1#1 : tensor<!tf.string>, tensor<2x!tf.string>
16 }) {device = "/device:CPU:0"} : () -> (tensor<!tf.string>, tensor<2x!tf.string>)
17 …// CHECK-DAG: %[[LAYOUT0:.*]] = "tf.TPUGetLayoutOp"(%[[COMPILE]]#1) {index = 0 : i64, is_output = …
18 …// CHECK-DAG: %[[LAYOUT1:.*]] = "tf.TPUGetLayoutOp"(%[[COMPILE]]#1) {index = 1 : i64, is_output = …
[all …]
|
| D | resource_op_lifting.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-resource-op-lifting | FILECHECK_OPTS=""…
8 // CHECK: %[[RES_HANDLE:[0-9]*]] = "tf.VarHandleOp"
9 …%0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf.resource<tensor<…
11 // CHECK: %[[RES_READ_VAL:[0-9]*]] = "tf.ReadVariableOp"(%[[RES_HANDLE]])
13 // CHECK: %[[COMPUTE_RES:[0-9]*]] = "tf.SomeComputation"(%[[RES_READ_VAL]])
19 …%2 = "tf.ReadVariableOp"(%0) {dtype = i32} : (tensor<*x!tf.resource<tensor<*xi32>>>) -> tensor<*xi…
20 %3 = "tf.SomeComputation"(%2) : (tensor<*xi32>) -> (tensor<*xi32>)
34 // CHECK: %[[RES_HANDLE:[0-9]*]] = "tf.VarHandleOp"
35 …%0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf.resource<tensor<…
38 // CHECK: %[[COMPUTE_RES:[0-9]*]] = "tf.SomeComputation"()
[all …]
|
| D | promote_resources_to_args.mlir | 1 // RUN: tf-opt %s -split-input-file -verify-diagnostics -tf-promote-resources-to-args | FILECHECK_O…
4 // CHECK-LABEL: func @main(%arg0: tensor<i1>, %arg1: tensor<f32> {tf.resource_name = "x"}) -> tenso…
6 // CHECK-NOT: "tf.VarHandleOp"
7 // CHECK-NOT: "tf.ReadVariableOp"
8 // CHECK: %[[ADD:[0-9]*]] = "tf.AddV2"(%arg1, %[[CONST:[0-9]*]])
9 // CHECK: %[[PACK:[0-9]*]] = "tf.Pack"(%[[CONST]], %[[ADD]])
11 %0 = "tf.Const"() {value = dense<4.200000e+01> : tensor<f32>} : () -> tensor<f32>
12 …%1 = "tf.VarHandleOp"() {container = "", shared_name = "x"} : () -> tensor<!tf.resource<tensor<f32…
13 %2 = "tf.ReadVariableOp"(%1) : (tensor<!tf.resource<tensor<f32>>>) -> tensor<f32>
14 %3 = "tf.AddV2"(%2, %0) : (tensor<f32>, tensor<f32>) -> tensor<f32>
[all …]
|
| D | tpu_space_to_depth_pass.mlir | 1 // RUN: tf-opt %s -split-input-file -tf-tpu-space-to-depth-pass | FileCheck %s
5 …tf.devices = {"/job:localhost/replica:0/task:0/device:CPU:0" = {}, "/job:localhost/replica:0/task:…
6 …tf.resource> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"}, %arg1: tensor<!tf.varia…
7 %0 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
8 %1 = "tf.Const"() {value = dense<2> : tensor<i32>} : () -> tensor<i32>
9 %2 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
10 …tf.While"(%2, %1, %2, %0, %1, %arg2, %arg4, %arg5, %arg6, %arg7) {_lower_using_switch_merge = true…
14 …tf.resource> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"}, %arg6: tensor<!tf.resou…
15 %0 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
16 // CHECK: %[[INPUT:.*]] = "tf.IteratorGetNext"
[all …]
|
| D | tpu-variable-runtime-reformatting.mlir | 1 // RUN: tf-opt %s -split-input-file -tf-tpu-variable-runtime-reformatting| FileCheck %s
5 !tf_res_f32 = type tensor<*x!tf.resource<tensor<f32>>>
6 !tf_res_md_f32 = type tensor<*x!tf.resource<tensor<3x3x1x32xf32>>> // Multi-dim f32
8 module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}…
10 // CHECK-SAME: %[[ARG0:.*]]: tensor<*x!tf.resource<tensor<f32>>> {tf.device = "/device:TPU:0"},
11 // CHECK-SAME: %[[ARG1:.*]]: tensor<*x!tf.resource<tensor<f32>>> {tf.device = "/device:TPU:1"},
12 …// CHECK-SAME: %[[ARG2:.*]]: tensor<*x!tf.resource<tensor<3x3x1x32xf32>>> {tf.device = "/device:TP…
13 …// CHECK-SAME: %[[ARG3:.*]]: tensor<*x!tf.resource<tensor<3x3x1x32xf32>>> {tf.device = "/device:TP…
14 func @main(%arg0: !tf_res_f32 {tf.device = "/device:TPU:0"},
15 %arg1: !tf_res_f32 {tf.device = "/device:TPU:1"},
[all …]
|
| D | tpu-merge-variables-with-execute.mlir | 1 // RUN: tf-opt -split-input-file -verify-diagnostics -tf-tpu-merge-variables-with-execute %s | File…
6 // CHECK-SAME: %[[ARG_0:.*]]: tensor<*x!tf.resource<tensor<32xf32>>>
7 // CHECK-SAME: %[[ARG_1:.*]]: tensor<*x!tf.resource<tensor<64xf32>>>
8 // CHECK-SAME: %[[ARG_2:.*]]: tensor<*x!tf.resource<tensor<16xf32>>>
10 …%arg0: tensor<*x!tf.resource<tensor<32xf32>>> {tf.device = "/job:localhost/replica:0/task:0/device…
11 …%arg1: tensor<*x!tf.resource<tensor<64xf32>>> {tf.device = "/job:localhost/replica:0/task:0/device…
12 …%arg2: tensor<*x!tf.resource<tensor<16xf32>>> {tf.device = "/job:localhost/replica:0/task:0/device…
13 // CHECK-NEXT: %[[ID_0:.*]] = "tf.IdentityN"(%[[ARG_0]])
14 %id0 = "tf.IdentityN"(%arg0) {device = "/job:localhost/replica:0/task:0/device:TPU:0"}
15 : (tensor<*x!tf.resource<tensor<32xf32>>>) -> tensor<*x!tf.resource<tensor<32xf32>>>
[all …]
|
| D | shape_inference.mlir | 1 // RUN: tf-opt %s -tf-shape-inference -verify-diagnostics | FileCheck %s
3 module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 130 : i32}…
6 // CHECK: %[[RESULT:.*]] = "tf.AddV2"
9 %0 = "tf.Cast"(%arg0) : (tensor<1xi32>) -> tensor<*xi32>
10 %1 = "tf.Cast"(%arg1) : (tensor<1xi32>) -> tensor<*xi32>
11 %2 = "tf.AddV2"(%0, %1) : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32>
17 // CHECK: %[[MUL:.*]] = "tf.Mul"{{.*}} (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
18 …// CHECK: %[[ADD:.*]] = "tf.Add"(%[[MUL]], %[[MUL]]) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1x…
20 %0 = "tf.Mul"(%arg0, %arg0) : (tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
21 %1 = "tf.Add"(%0, %0) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
[all …]
|
| D | readonly_references_to_resources.mlir | 1 // RUN: tf-opt -verify-diagnostics -tf-readonly-references-to-resources -split-input-file %s | File…
6 // CHECK: "tf.VarHandleOp"
7 // CHECK: "tf.ReadVariableOp"
8 …%val0 = "tf.VariableV2"() {_class = ["loc:@v"], container = "", device = "", shape = #tf.shape<96>…
9 %val1 = "tf.Identity"(%val0) : (tensor<96x!tf.f32ref>) -> tensor<96xf32>
18 // CHECK: "tf.VarHandleOp"
19 // CHECK: "tf.ReadVariableOp"
20 …%val0 = "tf.VariableV2"() {container = "", device = "", shape = #tf.shape<96>, shared_name = ""} :…
21 %val1 = "tf.Identity"(%val0) {_class = ["loc:@v"]} : (tensor<96x!tf.f32ref>) -> tensor<96xf32>
30 // CHECK: "tf.VarHandleOp"
[all …]
|
| /external/curl/packages/vms/ |
| D | config_h.com | 171 $ write tf ""
172 $ write tf -
174 $ write tf -
176 $ write tf -
180 $ write tf -
183 $ write tf -
361 $ write tf "#endif"
369 $ write tf "#ifndef ''key2'"
370 $ write tf "#define ''key2' 1"
371 $ write tf "#endif"
[all …]
|
| /external/tensorflow/tensorflow/go/op/ |
| D | wrappers.go | 23 import tf "github.com/tensorflow/tensorflow/tensorflow/go" packageName
29 func makeOutputList(op *tf.Operation, start int, output string) ([]tf.Output, int, error) {
34 list := make([]tf.Output, size)
46 …laSpmdShardToFullShape(scope *Scope, input tf.Output, manual_sharding string, full_shape tf.Shape)…
51 opspec := tf.OpSpec{
53 Input: []tf.Input{
73 func XlaSort(scope *Scope, input tf.Output) (output tf.Output) {
77 opspec := tf.OpSpec{
79 Input: []tf.Input{
98 func XlaRecv(scope *Scope, dtype tf.DataType, tensor_name string, shape tf.Shape) (tensor tf.Output…
[all …]
|
| /external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/ |
| D | structured_input.py | 23 import tensorflow.compat.v2 as tf namespace
27 class TestModule(tf.Module):
42 @tf.function(input_signature=[
43 tf.TensorSpec([1], tf.float32),
44 tf.TensorSpec([2], tf.float32)
55 @tf.function(input_signature=[[
56 tf.TensorSpec([], tf.float32),
57 tf.TensorSpec([], tf.float32),
69 @tf.function(input_signature=[{
70 'x': tf.TensorSpec([1], tf.float32),
[all …]
|
| /external/tensorflow/tensorflow/compiler/mlir/lite/tests/ |
| D | fuse-tftext.mlir | 1 // RUN: tf-opt -tfl-prepare-composite-funcs-tf -tfl-fuse-tftext=true %s | FileCheck %s
3 …tf.string> {tf._user_specified_name = "input"}) -> (tensor<?x!tf.string>, tensor<?xi64>) attribute…
4 %0 = "tf.Const"() {value = dense<[0, 1]> : tensor<2xi64>} : () -> tensor<2xi64>
5 %1 = "tf.Const"() {value = dense<[]> : tensor<0xi64>} : () -> tensor<0xi64>
6 %2 = "tf.Const"() {value = dense<true> : tensor<i1>} : () -> tensor<i1>
7 %3 = "tf.Const"() {value = dense<-1> : tensor<i32>} : () -> tensor<i32>
8 %4 = "tf.Const"() {value = dense<[[0], [1]]> : tensor<2x1xi64>} : () -> tensor<2x1xi64>
9 %5 = "tf.Const"() {value = dense<-1> : tensor<1xi32>} : () -> tensor<1xi32>
10 %6 = "tf.Const"() {value = dense<2> : tensor<1xi32>} : () -> tensor<1xi32>
11 %7 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
[all …]
|
| /external/blktrace/iowatcher/ |
| D | main.c | 156 static void alloc_mpstat_gld(struct trace_file *tf) in alloc_mpstat_gld() argument
160 if (tf->trace->mpstat_num_cpus == 0) in alloc_mpstat_gld()
163 ptr = calloc((tf->trace->mpstat_num_cpus + 1) * MPSTAT_GRAPHS, in alloc_mpstat_gld()
169 tf->mpstat_gld = ptr; in alloc_mpstat_gld()
243 struct trace_file *tf; in add_trace_file() local
245 tf = calloc(1, sizeof(*tf)); in add_trace_file()
246 if (!tf) { in add_trace_file()
250 tf->label = ""; in add_trace_file()
251 tf->filename = strdup(filename); in add_trace_file()
252 list_add_tail(&tf->list, &all_traces); in add_trace_file()
[all …]
|
| /external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
| D | not_supported.txt | 9 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf…
10 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf…
11 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.i…
12 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[1,1,1,3],is_arg_max=True,output_type=tf.i…
13 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf…
14 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf…
15 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.i…
16 arg_min_max/arg_min_max_input_dtype=tf.int32,input_shape=[2,3,4,5],is_arg_max=True,output_type=tf.i…
17 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.i…
18 arg_min_max/arg_min_max_input_dtype=tf.float32,input_shape=[2,3,3],is_arg_max=True,output_type=tf.i…
[all …]
|
| /external/tensorflow/tensorflow/examples/speech_commands/ |
| D | models.py | 24 import tensorflow as tf namespace
160 saver = tf.compat.v1.train.Saver(tf.compat.v1.global_variables())
190 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate')
193 weights = tf.compat.v1.get_variable(
195 initializer=tf.compat.v1.truncated_normal_initializer(stddev=0.001),
197 bias = tf.compat.v1.get_variable(name='bias',
198 initializer=tf.compat.v1.zeros_initializer,
200 logits = tf.matmul(fingerprint_input, weights) + bias
256 dropout_rate = tf.compat.v1.placeholder(tf.float32, name='dropout_rate')
259 fingerprint_4d = tf.reshape(fingerprint_input,
[all …]
|
| /external/tensorflow/tensorflow/python/keras/integration_test/ |
| D | forwardprop_test.py | 24 import tensorflow as tf namespace
29 with tf.autodiff.ForwardAccumulator(primals, tangents) as acc:
32 primals_out, unconnected_gradients=tf.UnconnectedGradients.ZERO)
38 flat_primals = tf.nest.flatten(primals)
39 tangent_mask = [tf.zeros_like(primal) for primal in flat_primals]
41 primal_vector = tf.reshape(primal, [-1])
42 primal_vector_length = tf.size(primal_vector)
44 for element_index in tf.range(primal_vector_length):
45 mask = tf.one_hot(element_index, primal_vector_length)
46 tangent_mask[primal_index] = tf.reshape(mask, tf.shape(primal))
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