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tensorflow/compiler/mlir/tensorflow/tests/tpu_partitioned_op_conversion.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 20 17:43:51 UTC 2023 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/raise-custom-ops.mlir
// WRAPPED-NEXT: tf_executor.island wraps "tfl.custom_tf" // WRAPPED-NEXT: ^bb0(%arg1: tensor<*xf32>, %arg2: tensor<186xf32>, %arg3: tensor<186xf32>): // WRAPPED-NEXT: %[[fq:.*]] = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg1, %arg2, %arg3) <{narrow_range = true, num_bits = 8 : i64}> {device = ""} : (tensor<*xf32>, tensor<186xf32>, tensor<186xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/saved_model_import_test.cc
// MLIR @main function corresponds to the TF function "main_original". OwningOpRef<ModuleOp> module_op = ParseModuleOpString(R"mlir( func.func private @main(%arg: tensor<1x2xf32>) -> (tensor<1x2xf32>) attributes {tf._original_func_name = "main_original"} { return %arg : tensor<1x2xf32> } )mlir"); ASSERT_TRUE(module_op); absl::flat_hash_map<FunctionName, FunctionAlias> function_aliases;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 07 03:47:17 UTC 2024 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/dilated-conv.mlir
%5 = "tf.BiasAdd"(%4, %arg2) : (tensor<1x128x128xf32>, tensor<128xf32>) -> tensor<1x128x128xf32> func.return %5 : tensor<1x128x128xf32> // CHECK-LABEL: testDilatedConvWithExpandSqueeze1 // CHECK-SAME: ([[INPUT:%.*]]: tensor<1x128x128xf32>, [[FILTER:%.*]]: tensor<5x5x1x1xf32>, [[BIAS:%.*]]: tensor<128xf32>) // CHECK-NEXT: [[AXIS:%.*]] = "tf.Const"() <{value = dense<3> : tensor<i32>}> : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 44.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir
%min = arith.constant dense<0.0> : tensor<16xf32> %max = arith.constant dense<255.0> : tensor<16xf32> %mini = "tf.Identity"(%min) : (tensor<16xf32>) -> tensor<16xf32> %maxi = "tf.Identity"(%max) : (tensor<16xf32>) -> tensor<16xf32> %fq = "tf.FakeQuantWithMinMaxVarsPerChannel"(%in, %mini, %maxi) {num_bits = 5, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<16xf32>, tensor<16xf32>) -> tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir
%min = arith.constant dense<0.0> : tensor<16xf32> %max = arith.constant dense<15.0> : tensor<16xf32> %mini = "tf.Identity"(%min) : (tensor<16xf32>) -> tensor<16xf32> %maxi = "tf.Identity"(%max) : (tensor<16xf32>) -> tensor<16xf32> %fq = "tf.FakeQuantWithMinMaxVarsPerChannel"(%in, %mini, %maxi) {num_bits = 3, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<16xf32>, tensor<16xf32>) -> tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/saved_model_export_test.cc
func.func @main(%arg: tensor<1x2xf32> {tf_saved_model.index_path = ["input_tensor:0"]}) -> (tensor<1x2xf32> {tf_saved_model.index_path = ["output_tensor:0"]}) attributes {tf.entry_function = {inputs = "input_tensor:0", outputs = "output_tensor:0"}, tf_saved_model.exported_names = ["main"]} { %0 = tf_executor.graph { tf_executor.fetch %arg : tensor<1x2xf32> } return %0 : tensor<1x2xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 20 11:11:25 UTC 2024 - 19.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
func.func @bias_adjust_pertensor(%arg0: tensor<1x2xf32>) -> (tensor<1x2xf32>) { %0 = "quantfork.stats"(%arg0) { layerStats = dense<[-1.28e-5, 1.27e-5]> : tensor<2xf32> } : (tensor<1x2xf32>) -> tensor<1x2xf32> %w = arith.constant dense<[[0.0, 1.0], [1.0, 2.0]]> : tensor<2x2xf32> %b = arith.constant dense<[0.0, 2.1473647e6]> : tensor<2xf32> %fc = "tfl.fully_connected"(%0, %w, %b) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
%cst_weights = arith.constant dense<2.0> : tensor<1024x512xf32> %cst_bias = arith.constant dense<4.0> : tensor<1024xf32> %0 = "tfl.fully_connected" (%cst_input, %cst_weights, %cst_bias) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<512xf32>, tensor<1024x512xf32>, tensor<1024xf32>) -> tensor<1024xf32> func.return %0 : tensor<1024xf32> // 1.0 * 2.0 * 512 + 4.0 = 1028.0
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0)