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Results 31 - 40 of 78 for 16xf32 (0.14 sec)
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tensorflow/compiler/mlir/lite/experimental/tac/execution_metadata_exporter_test.cc
%2 = "tfl.add"(%arg0, %arg3) {fused_activation_function = "RELU6", per_device_costs = {CPU = 5.0 : f32, GPU = 1.0 : f32}, tac.device = "GPU"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32> %3 = "tfl.pack"(%1, %2) {axis = 0 : i32, per_device_costs = {CPU = 2.0 : f32, GPU = -1.0 : f32}, values_count = 2 : i32, tac.device = "CPU"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 06:11:34 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/debugging/mlir_dump_test.cc
module{ func.func @main(%arg0: tensor<10xf32>) -> tensor<10xf32> { return %arg0 : tensor<10xf32> } func.func @func1(%arg0: tensor<10xf32>, %arg1: tensor<10xf32>) -> tensor<10xf32> { %0 = stablehlo.add %arg0, %arg1 : tensor<10xf32> %1 = stablehlo.add %arg0, %arg1 : tensor<10xf32> return %0 : tensor<10xf32> } })mlir";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:17:14 UTC 2024 - 6.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/device-transform-nnapi.mlir
module { // CHECK-LABEL: main func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> { %0 = "tfl.squared_difference"(%arg0, %arg1) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> func.return %0 : tensor<4xf32> // CHECK: [[VAL_0:%.*]] = tfl.sub %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/optimize-arg-operand-constraint.mlir
// CHECK-LABEL: func @main func.func @main(%arg0: tensor<1xf32>) -> tensor<1xf32> attributes {tf.entry_function = {inputs = "input", outputs = "output_node"}} { %0 = arith.constant dense<2.000000e+00> : tensor<f32> %1 = arith.constant dense<1.000000e+00> : tensor<f32> %2 = "tf.AddV2"(%arg0, %1) {T = "tfdtype$DT_FLOAT", device = "", name = "StatefulPartitionedCall/add"} : (tensor<1xf32>, tensor<f32>) -> tensor<1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 719 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/while_licm.mlir
// Some loop invariant math %li0 = "tf.Div"(%a, %b) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> %cst = arith.constant dense<22.0> : tensor<f32> %li1 = "tf.Mul"(%li0, %cst) : (tensor<4xf32>, tensor<f32>) -> tensor<4xf32> %final = "tf.Add"(%add, %li1) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> "tf.Yield"(%final, %sub) : (tensor<4xf32>, tensor<i32>) -> () }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 30 03:28:59 UTC 2022 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/tfl_while_op_licm.mlir
// CHECK: while_1([[ARG0:%[^ :]*]]: tensor<i32>, [[ARG1:%[^ :]*]]: tensor<1xf32>) func.func @while_1(%arg0: tensor<i32>, %arg1: tensor<1xf32>) -> tensor<1xf32> { // CHECK: [[CST:%[^ ]*]] = arith.constant dense<1> : tensor<i32> // CHECK: "tfl.while"([[ARG0]], [[ARG1]]) // CHECK: (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>) %0:2 = "tfl.while"(%arg0, %arg1) ( // cond {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 14:24:59 UTC 2022 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_colocate_splits.mlir
%a:2, %control1 = tf_executor.island wraps "tf.A"() {_class = ["loc:@class"]} : () -> (tensor<2xf32>, tensor<2xf32>) %s:2, %control2 = tf_executor.island wraps "tf.Split"(%c, %a#1) {num_split = 2 : i32} : (tensor<i32>, tensor<2xf32>) -> (tensor<1xf32>, tensor<1xf32>) tf_executor.fetch } func.return } // ----- // CHECK-LABEL: func @no_colocate_split_has_device
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 27 18:44:34 UTC 2023 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/default_quant_params.mlir
%4 = "tf.LayerNorm"(%a1, %a2, %a3, %a4) {_tfl_quant_trait = "fully_quantizable", device = ""} : (tensor<128x128xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xi32>) -> tensor<128x128xf32> "tfl.yield"(%4) : (tensor<128x128xf32>) -> () }) {_tfl_quant_trait = "fully_quantizable", device = ""} : (tensor<128x128xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xi32>) -> tensor<128x128xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_globals_to_ml_program.mlir
^bb1(%0: tensor<!tf_type.resource<tensor<?xf32>>>, %1: tensor<!tf_type.resource<tensor<?xf32>>>, %2: tensor<!tf_type.resource<tensor<?xf32>>>): "tf.AssignVariableOp"(%0, %arg0) : (tensor<!tf_type.resource<tensor<?xf32>>>, tensor<?xf32>) -> () cf.br ^bb1(%1, %2, %0 : tensor<!tf_type.resource<tensor<?xf32>>>, tensor<!tf_type.resource<tensor<?xf32>>>, tensor<!tf_type.resource<tensor<?xf32>>>) }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 24 21:57:26 UTC 2022 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op_weight_only.mlir
%1 = "tf.BiasAdd"(%0, %cst_0) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<6xf32>) -> tensor<*xf32> func.return %1: tensor<*xf32> } func.func private @composite_depthwise_conv2d_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.7K bytes - Viewed (0)