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Results 1 - 6 of 6 for 16x16xf32 (0.34 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
func.return %0 : tensor<8x16xf32> // CHECK-LABEL:minimum // CHECK: "tfl.minimum"(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32> } func.func @realDiv(%arg0: tensor<8x16xf32>, %arg1: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.RealDiv"(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>
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/tensorflow/tests/shape_inference.mlir
// CHECK-SAME: -> tensor<!tf_type.variant<tensor<16x1xf32>>> func.func @while_variant(%arg0: tensor<!tf_type.variant<tensor<16x1xf32>>>) -> tensor<!tf_type.variant> { // CHECK: tf.While // CHECK-SAME: -> tensor<!tf_type.variant<tensor<16x1xf32>>> %0 = "tf.While"(%arg0) {cond = @variant_cond_func, body = @variant_body_func, is_stateless = true} : (tensor<!tf_type.variant<tensor<16x1xf32>>>) -> tensor<!tf_type.variant>
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/lite/tests/ops.mlir
%split_dim_2 = arith.constant dense<1> : tensor<1xi32> %4, %5 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x2xf32>) %6:2 = "tfl.split"(%split_dim_2, %arg0) {num_splits = 2 : i32} : (tensor<1xi32>, tensor<16x4xf32>) -> (tensor<16x2xf32>, tensor<16x?xf32>)
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/prepare-composite-functions-tf.mlir
%11 = "tf.Floor"(%10#0) {device = ""} : (tensor<2x16xf32>) -> tensor<2x16xf32> %12 = "tf.Maximum"(%0, %11) {device = ""} : (tensor<f32>, tensor<2x16xf32>) -> tensor<2x16xf32> %13 = "tf.Minimum"(%12, %4) {device = ""} : (tensor<2x16xf32>, tensor<f32>) -> tensor<2x16xf32> %14 = "tf.Cast"(%13) {Truncate = false, device = ""} : (tensor<2x16xf32>) -> tensor<2x16xi32>
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/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/transforms/optimize.cc
// %cst = arith.constant dense<1.0> : tensor<16x16x4xf32> // %0 = "tfl.conv_2d"... // %1 = "tfl.add"(%0, %cst) : (tensor<16x16x4xf32>, tensor<16x16x4xf32>) // After this optimization: // %cst = arith.constant dense<1.0> : tensor<f32> // %0 = "tfl.conv_2d"... // %1 = "tfl.add"(%0, %cst) : (tensor<16x16x4xf32>, tensor<f32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0)