- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 98 for 200xf32 (0.26 sec)
-
tensorflow/compiler/mlir/lite/experimental/tac/tests/get-op-cost.mlir
func.return %1 : tensor<10x10x10xf32> } // ----- func.func @pack_CPU(%arg0: tensor<100xf32>, %arg1: tensor<100xf32>) -> tensor<2x100xf32> attributes {tac.device = "CPU", tac.interface_name = "func_2"} { // CHECK: tac.cost = 1.000000e+02 %0 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, tac.device = "CPU", values_count = 2 : i32} : (tensor<100xf32>, tensor<100xf32>) -> tensor<2x100xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:29:10 UTC 2022 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/pick-subgraphs.mlir
%1 = "tfl.reshape"(%0, %cst) : (tensor<200xf32>, tensor<2xi64>) -> tensor<2x100xf32> func.return %1 : tensor<2x100xf32> } func.func @func_0_CPU_FLOAT(%arg0: tensor<100xf32>, %arg1: tensor<100xf32>, %arg2: tensor<100xf32>) -> tensor<100xf32> attributes {tac.cost = 2.000000e+02 : f32, tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_0"} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/group_by_dialect.mlir
%4 = mhlo.constant dense<0.0> : tensor<200x10xf32> %13 = mhlo.constant dense<-0.0> : tensor<f32> %29 = mhlo.reduce(%4 init: %13) applies mhlo.add across dimensions = [1] : (tensor<200x10xf32>, tensor<f32>) -> tensor<200xf32> return } // CHECK: func @handles_mhlo_regions // CHECK: call [[name:@[^(]*]]( // CHECK: func [[name]]() // ----- func.func @handles_regions_that_use_arguments(%arg0: f32, %arg1: f32) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 28 23:43:21 UTC 2022 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/lower_tf.mlir
// CHECK-DAG: %[[EXP:.*]] = "tf.Exp"(%[[SHIFTED]]) : (tensor<2x3xf32>) -> tensor<2x3xf32> // CHECK-DAG: %[[SUM:.*]] = "tf.Sum"(%[[EXP]], %[[AXIS]]) <{keep_dims = true}> : (tensor<2x3xf32>, tensor<1xi64>) -> tensor<2x1xf32> // CHECK-DAG: %[[RESULT:.*]] = "tf.Div"(%[[EXP]], %[[SUM]]) : (tensor<2x3xf32>, tensor<2x1xf32>) -> tensor<2x3xf32> // CHECK: return %[[RESULT]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
%arg7: tensor<2048x640xf32>, %arg8: tensor<2048x640xf32>, %arg9: tensor<2048xf32>, %arg10: tensor<2048xf32>, %arg11: tensor<2048xf32>, %arg12: tensor<2048xf32>, %arg13: tensor<640x2048xf32>, %arg14: tensor<640xf32>, %arg15: tensor<2048xf32>, %arg16: tensor<2048xf32>, %arg17: tensor<2048xf32>, %arg18: tensor<2048xf32>, %arg19: tensor<1x640xf32>, %arg20: tensor<1x2048xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/lower-static-tensor-list.mlir
%0 = "tf.TensorListFromTensor"(%arg0, %arg1) : (tensor<3x10xf32>, tensor<1xi32>) -> tensor<!tf_type.variant<tensor<10xf32>>> %1 = "tf.TensorListPushBack"(%0, %arg2) : (tensor<!tf_type.variant<tensor<10xf32>>>, tensor<10xf32>) -> tensor<!tf_type.variant<tensor<10xf32>>> %2 = "tf.TensorListStack"(%1, %arg1) : (tensor<!tf_type.variant<tensor<10xf32>>>, tensor<1xi32>) -> tensor<?x10xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 39.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
%3 = "tfl.dequantize"(%2) : (tensor<2x3x!quant.uniform<i16:f32, 1.0>>) -> (tensor<2x3xf32>) %4 = "tfl.concatenation"(%1, %3) {axis = -1 : i32, fused_activation_function = "NONE"} : (tensor<2x1xf32>, tensor<2x3xf32>) -> tensor<2x4xf32> %5 = "tfl.add"(%4, %arg2) {fused_activation_function = "NONE"} : (tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<2x4xf32> func.return %5: tensor<2x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op_stablehlo.mlir
%3 = stablehlo.concatenate %2, %1, dim = 0 : (tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<2x3xf32> return %3 : tensor<2x3xf32> } func.func private @composite_dot_general_fn_1(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module, tf_quant.composite_function} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 18K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/default_quant_params.mlir
// CHECK-LABEL: hardcode_all func.func @hardcode_all(%arg0: tensor<2x2xf32>, %arg1: tensor<2x1xf32>) -> tensor<2x2xf32> { %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function="NONE"}: (tensor<2x2xf32>, tensor<2x1xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32> // CHECK: %[[q0:.*]] = "tfl.quantize"(%arg1) <{qtype = tensor<2x1x!quant.uniform<u8:f32, 0.0078431372549019607:128>>}>
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/lite/tests/optimize_op_order.mlir
func.func @no_pushdown_multiple_outputs(%arg0: tensor<1000x2x!quant.uniform<i8:f32, 7.812500e-03>>) -> tensor<1000xf32> { %0 = "tfl.dequantize"(%arg0) : (tensor<1000x2x!quant.uniform<i8:f32, 7.812500e-03>>) -> tensor<1000x2xf32> %1:2 = "tfl.unpack"(%0) {axis = 1 : i32, num = 2 : i32} : (tensor<1000x2xf32>) -> (tensor<1000xf32>, tensor<1000xf32>) func.return %1#0 : tensor<1000xf32> // CHECK-NEXT: tfl.dequantize // CHECK-NEXT: tfl.unpack }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 01 02:06:15 UTC 2022 - 3.6K bytes - Viewed (0)