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Results 1 - 10 of 33 for 1x2x4xi32 (0.3 sec)
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tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
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/tests/ops.mlir
// CHECK: "tfl.pack"(%arg0, %arg1) <{axis = -2 : i32, values_count = 2 : i32}> %0 = "tfl.pack"(%arg0, %arg1) {axis = -2 : i32, values_count = 2 : i32} : (tensor<1x4xi32>, tensor<1x4xi32>) -> tensor<1x2x4xi32> func.return %0 : tensor<1x2x4xi32> } func.func @packNegInputAxis3(%arg0: tensor<1x4xi32>, %arg1: tensor<1x4xi32>) -> tensor<2x1x4xi32> {
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/tensorflow/tests/batchmatmul_to_einsum.mlir
// CHECK-LABEL: test_batch_matmul_adj_to_einsum // CHECK: %[[RES_EINSUM:[0-9]*]] = "tf.Einsum"(%arg0, %arg1) <{equation = "...mk,...nk->...mn"}> : (tensor<1x2x3xf32>, tensor<4x3xf32>) -> tensor<1x2x4xf32> // CHECK: return %[[RES_EINSUM]] : tensor<1x2x4xf32> %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = false, adj_y = true} : (tensor<1x2x3xf32>, tensor<4x3xf32>) -> tensor<1x2x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fold_broadcast.mlir
%1 = mhlo.multiply %0, %cst1 : tensor<1x1x2x4xi32> // CHECK: return %[[RES]] : tensor<1x1x2x4xi32> func.return %1 : tensor<1x1x2x4xi32> } // CHECK-LABEL: @foldBroadcastInDimBeforeMulOp_bcast_dim_4D_int func.func @foldBroadcastInDimBeforeMulOp_bcast_dim_4D_int() -> tensor<1x2x1x4xi32> { // CHECK-DAG: %[[RES:.*]] = mhlo.constant dense<{{\[\[\[\[}}0, 1, 4, 9]], {{\[\[}}0, 1, 4, 9]]]]> : tensor<1x2x1x4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
%cst_0 = arith.constant dense<0> : tensor<1x2x3xi32> %cst_1 = arith.constant dense<1> : tensor<1x2x3xi32> %0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 2 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<1x2x6xi32> func.return %0 : tensor<1x2x6xi32> // CHECK: %[[CST:.*]] = arith.constant dense<[{{\[}}{{\[}}0, 0, 0, 1, 1, 1], {{\[}}0, 0, 0, 1, 1, 1]]]> : tensor<1x2x6xi32>
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/tf2xla/api/v2/legalize_tf_test.cc
func.func @main() -> (tensor<1x4x4xf32>) { %%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>
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/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK: %cst = arith.constant dense<2> : tensor<1xi32> // CHECK: %3 = "tfl.reduce_max"(%arg0, %cst) <{keep_dims = false}> : (tensor<2x2x4xf32>, tensor<1xi32>) -> tensor<2x2xf32> // CHECK: %4 = "tfl.arg_max"(%arg0, %cst) : (tensor<2x2x4xf32>, tensor<1xi32>) -> tensor<2x2xi32> // CHECK: return %3, %4 : tensor<2x2xf32>, tensor<2x2xi32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: %[[RESULT:.*]] = "tf.FloorMod"(%arg0, %arg1) : (tensor<192x8xi32>, tensor<192x8xi32>) -> tensor<192x8xi32> // CHECK: return %[[RESULT]] // CHECK: } func.func @convert_floor_mod_int(%arg0: tensor<192x8xi32>, %arg1: tensor<192x8xi32>) -> tensor<192x8xi32> { %0 = mhlo.constant dense<0> : tensor<192x8xi32> %1 = mhlo.remainder %arg0, %arg1 : tensor<192x8xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K 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)