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Results 1 - 10 of 76 for 2x5xi32 (0.14 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-with-tf2xla-hlo-importer.mlir
func.func @dynamic_update_slice(%arg0: tensor<3x4xi32>, %arg1: tensor<2x2xi32>, %arg2: tensor<2xi32>) -> tensor<3x4xi32> { // CHECK: %[[SLICE0:.*]] = "mhlo.slice"(%[[ARG2]]) // CHECK-DAG-SAME: start_indices = dense<0> : tensor<1xi64> // CHECK-DAG-SAME: limit_indices = dense<1> : tensor<1xi64> // CHECK-DAG-SAME: strides = dense<1> : tensor<1xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
} func.func @addN(%arg0: tensor<2x3xi32>, %arg1: tensor<2x3xi32>, %arg2: tensor<2x3xi32>) -> tensor<2x3xi32> { %0 = "tf.AddN"(%arg0, %arg1, %arg2) : (tensor<2x3xi32>, tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32> func.return %0 : tensor<2x3xi32> // CHECK-LABEL: addN // CHECK: "tfl.add_n"(%arg0, %arg1, %arg2) : (tensor<2x3xi32>, tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32> // CHECK: return }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%1 = "tfl.neg"(%arg0) : (tensor<2x3xf32>) -> tensor<2x3xf32> %2 = "tfl.relu"(%1) : (tensor<2x3xf32>) -> tensor<2x3xf32> %3 = "tfl.mul"(%alpha, %2) {fused_activation_function = "NONE"} : (tensor<f32>, tensor<2x3xf32>) -> tensor<2x3xf32> %4 = "tfl.add"(%0, %3) {fused_activation_function = "NONE"} : (tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf32> func.return %4 : tensor<2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
func.func @transpose_2d_identity() -> tensor<2x2xi32> { %cst = arith.constant dense<[[0, 1], [2, 3]]> : tensor<2x2xi32> %cst_perm = arith.constant dense<[0, 1]> : tensor<2xi32> // CHECK: %[[CST:.*]] = arith.constant dense<{{\[\[}}0, 1], {{\[}}2, 3]]> : tensor<2x2xi32> // CHECK: return %[[CST]] %0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<2x2xi32>, tensor<2xi32>) -> tensor<2x2xi32> func.return %0 : tensor<2x2xi32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
// CHECK-DAG: %[[EXP:.*]] = "tf.Exp"(%[[SHIFTED]]) : (tensor<2x3xf32>) -> tensor<2x3xf32> // CHECK-DAG: %[[SUM:.*]] = "tf.Sum"(%[[EXP]], %[[AXIS]]) <{keep_dims = true}> : (tensor<2x3xf32>, tensor<1xi64>) -> tensor<2x1xf32> // CHECK-DAG: %[[RESULT:.*]] = "tf.Div"(%[[EXP]], %[[SUM]]) : (tensor<2x3xf32>, tensor<2x1xf32>) -> tensor<2x3xf32> // CHECK: return %[[RESULT]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%8 = stablehlo.convert %7 : (tensor<1x2xi32>) -> tensor<1x2xf32> %9 = stablehlo.convert %2 : (tensor<2x3xi8>) -> tensor<2x3xf32> %10 = stablehlo.dot_general %8, %9, contracting_dims = [1] x [0] : (tensor<1x2xf32>, tensor<2x3xf32>) -> tensor<1x3xf32> %11 = stablehlo.convert %3 : (tensor<1x3xi32>) -> tensor<1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
} func.func @_func(%arg0: tensor<2x4xf32>, %arg1: tensor<4x2xf32>) -> tensor<2x2xf32> { %0 = "tf.MatMul"(%arg0, %arg1) {_XlaSharding = "\08\03\1A\02\02\01\22\02\00\01"} : (tensor<2x4xf32>, tensor<4x2xf32>) -> tensor<2x2xf32> %1 = "tf.Identity"(%0) : (tensor<2x2xf32>) -> tensor<2x2xf32> return %1 : tensor<2x2xf32> } // ----- // The following op sharding is used in the following test case:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 20 19:07:52 UTC 2024 - 47.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
func.return %0 : tensor<2x2xi32> } // ----- func.func @unpack(%arg0: tensor<2x3xi32>) -> tensor<2xi32> { // CHECK: "tfl.unpack"(%arg0) <{axis = 1 : i32, num = 3 : i32}> %0:3 = "tfl.unpack"(%arg0) {axis = 1 : i32, num = 3 : i32} : (tensor<2x3xi32>) -> (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) func.return %0#0 : tensor<2xi32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
func.func @RemoveRedundantUnpackPack(%arg0: tensor<2x5xf32>) -> tensor<2x5xf32> { %0:2 = "tfl.unpack"(%arg0) {axis = 0 : i32, num = 2 : i32} : (tensor<2x5xf32>) -> (tensor<5xf32>, tensor<5xf32>) %1 = "tfl.pack"(%0#0, %0#1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<5xf32>, tensor<5xf32>) -> (tensor<2x5xf32>) func.return %1: tensor<2x5xf32> // CHECK-NOT: pack // CHECK: return %arg0 : tensor<2x5xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_space_to_depth_pass.mlir
%9 = "tf.Const"() {value = dense<-1> : tensor<1xi32>} : () -> tensor<1xi32> %10 = "tf.Const"() {value = dense<[[0, 0], [3, 3], [3, 3], [0, 0]]> : tensor<4x2xi32>} : () -> tensor<4x2xi32> %11 = "tf.Pad"(%arg0, %10) : (tensor<2x224x224x3xf32>, tensor<4x2xi32>) -> tensor<2x230x230x3xf32> %12 = "tf.Cast"(%arg1) {Truncate = false} : (tensor<2x1xf32>) -> tensor<2x1xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 37.4K bytes - Viewed (0)