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Results 51 - 58 of 58 for 5x11xf32 (0.19 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/target-annotation.mlir
%2 = "tfl.relu"(%arg0) : (tensor<1xf32>) -> tensor<1xf32> // CHECK: tac.device = "CPU", tac.inference_type = "FLOAT" %3 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32> func.return } func.func @notAnnotateConst(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> { // CHECK-NOT: tac.device tac.inference_type
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 19:32:06 UTC 2023 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
For example, if we have the code ```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
func.return %0 : tensor<8x16xf32> } // ----- func.func @testCumprod(%arg: tensor<8x16xf32>) -> tensor<8x16xf32> { %axis = arith.constant dense<-3> : tensor<i32> // expected-error @+1 {{axis operand should be within range [-2, 2)}} %0 = "tf.Cumprod"(%arg, %axis) : (tensor<8x16xf32>, tensor<i32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
// expected-error @+1 {{expect 'output' num_elements % 40 == 0, got 'tensor<1x41xf32>'}} %0 = "tfl.fully_connected"(%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x37xf32>, tensor<40x37xf32>, tensor<40xf32>) -> tensor<1x41xf32> func.return %0 : tensor<1x41xf32> } // -----
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/tensor_list_ops_decomposition.mlir
// CHECK: %[[IND_RESHPE:.*]] = "tf.Reshape"(%[[ARG1]], %[[IND_SHAPE]]) : (tensor<5xi32>, tensor<2xi32>) -> tensor<5x1xi32> // CHECK: %[[SC:.*]] = "tf.TensorScatterUpdate"(%[[BUFFER]], %[[IND_RESHPE]], %[[ARG2]]) : (tensor<10x8x9xf32>, tensor<5x1xi32>, tensor<5x8x9xf32>) -> tensor<10x8x9xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 38.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
}) {is_stateless = false} : (tensor<i32>, tensor<!tf_type.variant<tensor<?x1xf32>>>) -> (tensor<i32>, tensor<!tf_type.variant<tensor<?x1xf32>>>) %elem_1 = "tf._SomeOtherOp"() : () -> tensor<8x1xf32> %tl_set_item = "tf.TensorListSetItem"(%while#1, %one, %elem_1) : (tensor<!tf_type.variant<tensor<?x1xf32>>>, tensor<i32>, tensor<8x1xf32>) -> tensor<!tf_type.variant<tensor<?x1xf32>>> func.return }
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/tf2xla/transforms/legalize_tf.cc
// (tensor<4x1xf32>, tensor<4x2xf32>, tensor<4x3xf32>) // // We will generate slices following slices: // %0 = "mhlo.slice"(%input) { // limit_indices = dense<[4, 1]> : tensor<2xi64>, // start_indices = dense<0> : tensor<2xi64>, // strides = dense<1> : tensor<2xi64>} : // (tensor<4x6xf32>) -> tensor<4x1xf32> // %1 = "mhlo.slice"(%input) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)