- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 15 for 2x4x6x7xf32 (0.14 sec)
-
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir
} func.func @einsum_reshapetail(%arg0: tensor<3x4x5xf32>, %arg1: tensor<5x6x2xf32>) -> tensor<3x4x6x2xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "bfd,dnh->bfnh"}: (tensor<3x4x5xf32>, tensor<5x6x2xf32>) -> tensor<3x4x6x2xf32> func.return %0 : tensor<3x4x6x2xf32> // CHECK-LABEL: einsum_reshapetail // CHECK-DAG: %[[cst:.*]] = arith.constant dense<[5, 12]> : tensor<2xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 25.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
// CHECK-SAME: %arg0: tensor<2x4x4x1xf32>, // CHECK-SAME: %arg1: tensor<2x4x4x2xf32>) -> tensor<2x4x4x1xf32> attributes {tf._implements = "DenseImageWarp"} { // CHECK-NEXT: %0 = "tfl.custom"(%arg0, %arg1) <{custom_code = "DenseImageWarp", custom_option = #tfl<const_bytes : "0x">}> : (tensor<2x4x4x1xf32>, tensor<2x4x4x2xf32>) -> tensor<2x4x4x1xf32> // CHECK-NEXT: return %0 : tensor<2x4x4x1xf32> // CHECK-NEXT: } } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/aliasing_arg_attr.mlir
attributes {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} { %0:2 = tf_executor.graph { %1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) {T = ["tfdtype$DT_FLOAT", "tfdtype$DT_INT32"], device = "", name = "identity"} : (tensor<*xf32>, tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 958 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/device-arg-retval-attr.mlir
attributes {tf.entry_function = {inputs = "args_0,args_1", outputs = "rets_0,rets_1"}} { %0:2 = tf_executor.graph { %1:3 = tf_executor.island wraps "tf.IdentityN"(%arg0, %arg1) {T = ["tfdtype$DT_FLOAT", "tfdtype$DT_INT32"], device = "", name = "identity"} : (tensor<*xf32>, tensor<2x4x6x8xi32>) -> (tensor<*xf32>, tensor<2x4x6x8xi32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 1.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/unique_output_name.mlir
module attributes {tf.versions = {producer = 946 : i32}, tf_saved_model.semantics, tfl.description = "MLIR Converted.", tfl.schema_version = 3 : i32} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/push-tpose-through-ewise.mlir
// ----- // CHECK-LABEL: doubleTposeInputPermNotEqualNoChange func.func @doubleTposeInputPermNotEqualNoChange(%arg0: tensor<2x4x3x5xf32>, %arg1: tensor<2x3x4x5xf32>) -> tensor<5x2x3x4xf32> { %perm = arith.constant dense<[3, 0, 2, 1]> : tensor<4xi32> %0 = "tfl.transpose"(%arg0, %perm) : (tensor<2x4x3x5xf32>, tensor<4xi32>) -> tensor<5x2x3x4xf32> %perm1 = arith.constant dense<[3, 0, 1, 2]> : tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/graph-as-function.mlir
// RUN: tf-mlir-translate -mlir-to-graphdef %s -tf-graph-as-function -o - | FileCheck %s func.func @main(%arg0: tensor<*x!tf_type.resource>, %arg1: tensor<*x!tf_type.resource<tensor<3x3x1x32xf32>>>, %arg2: tensor<*xf32>, %arg3: tensor<2x4x6x8xi32>) -> (tensor<f32>, tensor<f32>) attributes {tf.entry_function = {inputs = "args_0,args_1,args_2,args_3", outputs = "rets_0_RetVal,rets_1_RetVal"}} { %graph:2 = tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 12:28:56 UTC 2022 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir
%20 = "tf.Mul"(%19, %cst_0) {device = ""} : (tensor<2x4x3x6xf32>, tensor<f32>) -> tensor<2x4x3x6xf32> %21 = "tf.Relu"(%20) {device = ""} : (tensor<2x4x3x6xf32>) -> tensor<2x4x3x6xf32> %22 = "tf.Minimum"(%21, %cst) {device = ""} : (tensor<2x4x3x6xf32>, tensor<f32>) -> tensor<2x4x3x6xf32> %23 = "tf.Identity"(%22) {device = ""} : (tensor<2x4x3x6xf32>) -> tensor<2x4x3x6xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 81K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
// CHECK: return %[[RESULT]] : tensor<2x3x4x6xf32> } // ----- func.func @batchMatMulTwoDimAdjXY(%arg0: tensor<2x3x5x4xf32>, %arg1: tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> { %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = true, adj_y = true} : (tensor<2x3x5x4xf32>, tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> func.return %0 : tensor<2x3x4x6xf32> // CHECK-LABEL: batchMatMulTwoDimAdjXY
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0)