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tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/output-shapes-attr.mlir
func.func @main(%arg0: tensor<10xi32>) -> tensor<10xi32> attributes {tf.entry_function = {inputs = "input0", outputs = "output0"}} { %graph = tf_executor.graph { tf_executor.fetch %arg0 : tensor<10xi32> } func.return %graph : tensor<10xi32> } // CHECK: node { // CHECK-NEXT: name: "input0" // CHECK-NEXT: op: "_Arg" // CHECK: key: "T" // CHECK-NEXT: value {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 3.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/tf_to_corert_pipeline.mlir
@__forward_call_369(%arg0: tensor<16x224x224x3xf32> {tf._user_specified_name = "inputs"}, %arg1: tensor<*x!tf_type.resource>, %arg2: tensor<*x!tf_type.resource>, %arg3: tensor<*x!tf_type.resource>, %arg4: tensor<*x!tf_type.resource>) -> (tensor<?x?xf32>, tensor<*xf32>, tensor<?x16384xf32>, tensor<16x112x112x?xf32>, tensor<16x224x224x3xf32>, tensor<*xf32>) attributes {tf.entry_function = {control_outputs = "", inputs = "inputs_0,conv1_conv2d_readvariableop_resource,conv1_biasadd_readvariableop_resource...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/device_compiler_test_helper.cc
RunOptions run_options; Tensor input_a = CreateInputTensor(shape, 0); Tensor input_b = CreateInputTensor(shape, shape.num_elements()); Tensor input_c = CreateInputTensor(shape, 2 * shape.num_elements()); TF_RETURN_IF_ERROR(session->Run( run_options, {std::make_pair("a", input_a), std::make_pair("b", input_b), std::make_pair("c", input_c)}, {"m"}, {}, &golden_output_tensors, nullptr));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Feb 09 08:24:16 UTC 2024 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/switch_n.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 15 19:42:47 UTC 2021 - 3.7K bytes - Viewed (0) -
tensorflow/cc/framework/ops.cc
} Operation::Inputs Operation::GetInputs(Node* node) { Operation::Inputs inputs; if (node != nullptr) { inputs.resize(node->num_inputs(), {nullptr, -1}); for (const Edge* e : node->in_edges()) { if (e->IsControlEdge()) continue; inputs[e->dst_input()] = std::make_pair(e->src(), e->src_output()); } } return inputs; } Input::Initializer::Initializer(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 11 01:20:50 UTC 2021 - 3.5K bytes - Viewed (0) -
tensorflow/cc/ops/while_loop_test.cc
const std::vector<T>& expected_output_values) { ClientSession session(scope_); DCHECK_EQ(input_values.size(), inputs_.size()); ClientSession::FeedType feeds; for (int i = 0; i < inputs_.size(); ++i) { feeds.emplace(inputs_[i], input_values[i]); } std::vector<Tensor> out_tensors; TF_ASSERT_OK(session.Run(feeds, outputs_, &out_tensors));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 13 22:30:58 UTC 2023 - 6.4K bytes - Viewed (0) -
src/main/java/org/codelibs/fess/suggest/converter/KatakanaConverter.java
readingList.add(toKatakana(text)); return readingList; } protected String toKatakana(final String inputStr) throws IOException { final StringBuilder kanaBuf = new StringBuilder(); final Reader rd = new StringReader(inputStr); try (TokenStream stream = createTokenStream(rd)) { if (stream == null) { throw new IOException("Invalid tokenizer.");
Registered: Wed Jun 12 15:38:08 UTC 2024 - Last Modified: Thu Feb 22 01:36:54 UTC 2024 - 4.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_device_ops.mlir
%result:4 = tf_device.replicate([%arg0, %arg1] as %input0: tensor<*xf32>) {n = 2 : i32} { tf_device.return %input0, %arg2 : tensor<*xf32>, tensor<*xi32> } func.return // CHECK: tf_device.replicate // CHECK-SAME: ([%[[ARG_0]], %[[ARG_1]]] as %[[INPUT_0:[a-z0-9]*]]: tensor<*xf32>) // CHECK-SAME: n = 2 // CHECK-NEXT: tf_device.return %[[INPUT_0]], %[[ARG_2]] } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 23:53:20 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/simple-graph.mlir
module { func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> attributes {tf.entry_function = {inputs = "input0,input1,input2,input3", outputs = "output"}} { %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu-annotate-dynamic-shape-inputs.mlir
// RUN: tf-opt -split-input-file -verify-diagnostics -tf-tpu-annotate-dynamic-shape-inputs %s | FileCheck %s // Test that annotate the inputs of the cluster func to be dynamic shaped. module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} { func.func @main( %arg0: tensor<2048xi64> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Aug 14 15:35:49 UTC 2023 - 2.3K bytes - Viewed (0)