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Results 1 - 10 of 16 for 1x6x2xi32 (0.54 sec)
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tensorflow/compiler/mlir/lite/tests/shape-inference.mlir
func.func @testReshapeShapeInference(%arg0: tensor<3x4xi32>) -> tensor<*xi32> { %cst = arith.constant dense<[1, 6, 2]> : tensor<3xi32> // CHECK: "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<1x6x2xi32> %0 = "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<*xi32> func.return %0 : tensor<*xi32> } } // ----- // CHECK-LABEL: testReshapeShapeInferenceUnknownDim
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
// CHECK-NEXT: return %0 : tensor<2x3x2x2xi32> // CHECK-NEXT:} func.func @transpose(%arg0: tensor<2x3x2xi32>) -> tensor<2x3x2xi32> { %0 = "vhlo.transpose_v1"(%arg0) <{permutation = #vhlo.tensor_v1<dense<[2, 1, 0]> : tensor<3xi64>>}> : (tensor<2x3x2xi32>) -> tensor<2x3x2xi32> return %0 : tensor<2x3x2xi32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%8 = stablehlo.convert %7 : (tensor<1x4x2xi8>) -> tensor<1x4x2xf32> %9 = stablehlo.convert %2 : (tensor<2x3xi8>) -> tensor<2x3xf32> %10 = stablehlo.dot_general %8, %9, contracting_dims = [2] x [0] : (tensor<1x4x2xf32>, tensor<2x3xf32>) -> tensor<1x4x3xf32> %11 = stablehlo.convert %3 : (tensor<1x1x3xi32>) -> tensor<1x1x3xf32> %12 = stablehlo.broadcast_in_dim %11, dims = [0, 1, 2] : (tensor<1x1x3xf32>) -> tensor<1x4x3xf32> // Optional
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/lite/tests/const-fold.mlir
func.func @concatConstantTensorsMiddleDim() -> tensor<1x4x3xi32> { %cst_0 = arith.constant dense<0> : tensor<1x2x3xi32> %cst_1 = arith.constant dense<1> : tensor<1x2x3xi32> %0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 1 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<1x4x3xi32> func.return %0 : tensor<1x4x3xi32>
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/stack_ops_decomposition.mlir
// CHECK-NEXT: %[[UPDATE:.*]] = "tf.XlaDynamicUpdateSlice"(%[[STACK_VAL]], %[[UPDATE_SLICE]], %[[CONCAT_OFFETS]]) : (tensor<10x2xi32>, tensor<1x2xi32>, tensor<2xi32>) -> tensor<10x2xi32> // CHECK-NEXT: "tf.AssignVariableOp"(%[[BUFFER]], %[[UPDATE]]) : (tensor<!tf_type.resource<tensor<10x2xi32>>>, tensor<10x2xi32>) -> () // CHECK-NEXT: %[[CONST1:.*]] = "tf.Const"() <{value = dense<1> : tensor<1xi32>}> : () -> tensor<1xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 25.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_sharding_identification.mlir
// Use a four dimension sharding (devices=[1,1,1,1]0) // Since the input tensor only has three dimensions, we expect this to fail. %0 = "tf.XlaSharding"(%arg0) { _XlaSharding = "\08\03\1A\04\01\01\01\01\22\01\00" } : (tensor<1x2x3xi32>) -> tensor<1x2x3xi32> %1 = "tf.A"(%0) : (tensor<1x2x3xi32>) -> (tensor<1x2x3xi32>) func.return %1: tensor<1x2x3xi32> } // ----- // CHECK-LABEL: func @check_retval_sharding_errors
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/dilated-conv.mlir
%cst = "tf.Const"() {value = dense<0> : tensor<1x2xi32>} : () -> tensor<1x2xi32> %cst_0 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32> %cst_1 = "tf.Const"() {value = dense<2> : tensor<1xi32>} : () -> tensor<1xi32> %cst_2 = "tf.Const"() {value = dense<4> : tensor<1x2xi32>} : () -> tensor<1x2xi32> %0 = "tf.SpaceToBatchND"(%arg0, %cst_1, %cst_2) : (tensor<1x128x3xf32>, tensor<1xi32>, tensor<1x2xi32>) -> tensor<2x68x3xf32>
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/tf2xla/tests/legalize-tf-binary-elementwise.mlir
// fixed upstream). func.func @broadcast_add(%arg0: tensor<1xi32>, %arg1: tensor<1x2xi32>) -> tensor<1x2xi32> { // CHECK-NEXT: %[[LHS_BCAST:.+]] = "mhlo.broadcast_in_dim"(%arg0) <{broadcast_dimensions = dense<1> : tensor<1xi64>}> // CHECK-NEXT: mhlo.add %[[LHS_BCAST]], %arg1 %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<1xi32>, tensor<1x2xi32>) -> tensor<1x2xi32> func.return %0: tensor<1x2xi32> } // CHECK-LABEL: func @broadcast_multi_dim_add
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf_test.cc
%%arg0 = "tf.Const"() {value = dense<-3.0> : tensor<1x4x2xf32>} : () -> tensor<1x4x2xf32> %%arg1 = "tf.Const"() {value = dense<-3.0> : tensor<1x2x4xf32>} : () -> tensor<1x2x4xf32> %%1 = "tf.%s"(%%arg0, %%arg1) {T = f32, adj_x = false, adj_y = false, grad_x = false, grad_y = false, device = ""} : (tensor<1x4x2xf32>, tensor<1x2x4xf32>) -> tensor<1x4x4xf32> func.return %%1 : tensor<1x4x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 13 23:59:33 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_space_to_depth_pass.mlir
%1 = "tf.Const"() {value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32> %2 = "tf.Const"() {value = dense<-1> : tensor<i32>} : () -> tensor<i32> %3 = "tf.Const"() {value = dense<[[0, 1]]> : tensor<1x2xi32>} : () -> tensor<1x2xi32> %4 = "tf.Const"() {value = dense<> : tensor<0xi32>} : () -> tensor<0xi32> %5 = "tf.Const"() {value = dense<2.500000e-01> : tensor<f32>} : () -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 37.4K bytes - Viewed (0)