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Results 31 - 40 of 57 for 1x2xf32 (0.42 sec)
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tensorflow/compiler/mlir/tensorflow/tests/device_assignment_by_func_attr.mlir
// CHECK: device = "cpu" %2 = "tf.Relu"(%1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "cpu"} : (tensor<3x3xf32>) -> tensor<3x3xf32> // CHECK: device = "xpu" %3 = "tf.Relu"(%2) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"]} : (tensor<3x3xf32>) -> tensor<3x3xf32> func.return %3 : tensor<3x3xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 10 00:30:05 UTC 2022 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize-tfl-stablehlo-broadcast.mlir
module { func.func @main(%arg0: tensor<1x2xi32>) -> tensor<1x2x2xi32> { %0 = "tfl.custom"(%arg0) {custom_code = "stablehlo.broadcast_in_dim", custom_option = #tfl<const_bytes : "0x62726F6164636173745F64696D656E73696F6E73000201020119010101072C022401">} : (tensor<1x2xi32>) -> tensor<1x2x2xi32> func.return %0 : tensor<1x2x2xi32> } } // CHECK: module { // CHECK-NEXT: func @main(%arg0: tensor<1x2xi32>) -> tensor<1x2x2xi32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 16 05:09:09 UTC 2022 - 704 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/fold_constant_transpose.mlir
func.func @transpose_simple_1d() -> tensor<2xf32> { %0 = stablehlo.constant dense<[0.000000e+0, 1.000000e+0]> : tensor<2xf32> %1 = stablehlo.transpose %0, dims = [0] : (tensor<2xf32>) -> tensor<2xf32> return %1 : tensor<2xf32> } // CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant dense<[0.000000e+00, 1.000000e+00]> : tensor<2xf32> // CHECK-NOT: transpose // CHECK: return %[[CONST_0]] : tensor<2xf32> // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 08:06:02 UTC 2024 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/fallback.mlir
%1 = "tf.MatMul"(%arg0, %0) {T = f32, device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> func.return %1 : tensor<3x3xf32> } // CHECK-LABEL: func @gpu_device func.func @gpu_device(%arg0: tensor<3x1xf32>, %arg1: tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<3x3xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/remove_init_variable_v1.py
# CHECK-NEXT: [[R0:%.*]] = "tf.ReadVariableOp"([[ARG1]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: [[R1:%.*]] = "tf.MatMul"([[ARG0]], [[R0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return [[R1]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]]) y = tf.compat.v1.get_variable( name='y',
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/reshape.mlir
// Confirm we can extract type info from reshape func.func @main() -> tensor<2x2xf32> { // CHECK: %[[cst:.*]] = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32> // CHECK: %{{.*}} = "tfl.reshape"(%{{.*}}, %[[cst]]) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32> %cst = arith.constant dense<[2, 2]> : tensor<2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 730 bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/tests/rewrite_quantized_io.mlir
%arg1: tensor<1x5xf32>) -> (tensor<1x10x!quant.uniform<i8:f32, 0.2:42>>, tensor<1x5xf32>) { %0 = "tf.MyRequantize"(%arg0) : (tensor<1x10x!quant.uniform<i8:f32, 0.1:-128>>) -> tensor<1x10x!quant.uniform<i8:f32, 0.2:42>> %1 = "tf.Intermediate"(%arg1) : (tensor<1x5xf32>) -> tensor<1x5xf32> func.return %0, %1 : tensor<1x10x!quant.uniform<i8:f32, 0.2:42>>, tensor<1x5xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_update_embedding_enqueue_op_inputs.mlir
%arg2 :tensor<?x2xi32>, %arg3: tensor<?xi32>, %arg4: tensor<?xi32>, %arg5: tensor<?xi32>, %arg6: tensor<!tf_type.string>, %arg7: tensor<!tf_type.string>) -> () { // CHECK: %[[CONST_0:.*]] = "tf.Const"() %0 = "tf.Const"() {value = dense<[]> : tensor<0xf32>} : () -> tensor<0xf32> %2 = "tf.Const"() {value = dense<0.0> : tensor<2x2xf32>} : () -> tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/bucketize.mlir
// CHECK-EMPTY: %0 = "tfl.pseudo_const" () {value = dense<[[-5.0, 10000.0], [150.0, 10.0], [5.0, 100.0]]> : tensor<3x2xf32>} : () -> tensor<3x2xf32> loc("Const") %1 = "tfl.bucketize"(%0) {boundaries = [0.0 : f32, 10.0 : f32, 100.0 : f32]} : (tensor<3x2xf32>) -> tensor<3x2xi32> loc("bucketize") func.return %1 : tensor<3x2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/bucketize.mlir
func.func @main(%arg0: tensor<3x2xf32>) -> tensor<3x2xi32> { // CHECK-LABEL: @main // CHECK: "tfl.bucketize"(%arg0) <{boundaries = [0.000000e+00 : f32, 1.000000e+01 : f32, 1.000000e+02 : f32]}> : (tensor<3x2xf32>) -> tensor<3x2xi32> %0 = "tfl.bucketize"(%arg0) {boundaries = [0.0 : f32, 10.0 : f32, 100.0 : f32]} : (tensor<3x2xf32>) -> tensor<3x2xi32> func.return %0 : tensor<3x2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 571 bytes - Viewed (0)