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Results 31 - 39 of 39 for 9x10xf32 (0.43 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tpu_cluster_formation.mlir
%2 = "tf.Add"(%1, %1) { _xla_compile_device_type = "TPU", _replication_info = "cluster", device = "/task:0/device:TPU:0", dtype = f32 } : (tensor<1x80xf32>, tensor<1x80xf32>) -> tensor<1x80xf32> %3 = "tf.ResourceGatherNd"(%arg0, %0) { Tindices = i32 } : (tensor<*x!tf_type.resource<tensor<80xf32>>>, tensor<i32>) -> tensor<1x80xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 22:03:30 UTC 2024 - 53.9K 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/stablehlo/tests/optimize.mlir
%0 = "mhlo.reshape"(%arg0) : (tensor<1x1x512xf32>) -> tensor<1x512xf32> %1 = "mhlo.dot"(%0, %arg1) : (tensor<1x512xf32>, tensor<512x13x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x13xf32> %2 = "mhlo.reshape"(%1) : (tensor<1x13xf32>) -> tensor<1x1x13xf32> func.return %2 : tensor<1x1x13xf32> // CHECK: %[[RES:.*]] = "mhlo.dot_general"(%arg0, %arg1) <{ // CHECK-SAME: dot_dimension_numbers = #mhlo.dot<
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
%0 = "tfl.fully_connected"(%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<2x2x10xf32>, tensor<40x40xf32>, none) -> tensor<1x40xf32> func.return %0 : tensor<1x40xf32> } // ----- func.func @testFullyConnectedWith3DFilter(%arg0: tensor<1x37xf32>, %arg1: tensor<40x2x37xf32>, %arg2: tensor<40xf32>) -> tensor<1x40xf32> {
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-tf.mlir
%2 = "tf.Transpose"(%1, %cst_0): (tensor<1x2xf32>, tensor<2xi32>) -> tensor<2x1xf32> func.return %2 : tensor<2x1xf32> // CHECK: %cst = arith.constant // CHECK: %[[trans:.*]] = "tf.Transpose" // CHECK-SAME: -> tensor<2x1xf32> // CHECK: %[[q:.*]] = "tfl.quantize"(%[[trans]]) <{qtype = tensor<2x1x!quant.uniform<u8:f32, 1.000000e+00>>}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
func.func @torch_index_select(%arg0: tensor<2x1xf32>, %arg1: tensor<2xi32>) -> tensor<2x1xf32> { %0 = "mhlo.torch_index_select"(%arg0, %arg1) { batch_dims = 0 : i64, dim = 0 : i64 } : (tensor<2x1xf32>, tensor<2xi32>) -> tensor<2x1xf32> func.return %0 : tensor<2x1xf32> } // CHECK-LABEL: func @lowered_cumsum( // CHECK-SAME: %[[VAL_0:.*]]: tensor<4x12xf32>) -> tensor<4x12xf32> {
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/canonicalize.mlir
// CHECK: return %0 } // CHECK-LABEL: testAddOfNegRight func.func @testAddOfNegRight(%arg0: tensor<8x16xf32>, %arg1: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Neg"(%arg1) : (tensor<8x16xf32>) -> tensor<8x16xf32> %1 = "tf.Add"(%arg0, %0) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 132.1K 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) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
mlir_module = '''python func @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> { %add = "magic.op"(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32> return %ret : tensor<10x10xf32> } ''' @tf.function def foo(x, y): return mlir_passthrough_op([x, y], mlir_module, Toutputs=[tf.float32])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)