- Sort Score
- Result 10 results
- Languages All
Results 31 - 40 of 126 for 7x9xf32 (0.13 sec)
-
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
} // CHECK-LABEL: QuantizeConcat func.func @QuantizeConcat(tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2x!quant.uniform<u8:f32, 1.000000e-01:128>> { ^bb0(%arg0: tensor<1x2xf32>, %arg1: tensor<1x2xf32>): %0 = "tfl.concatenation"(%arg0, %arg1) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/pre_calibration_test.cc
module attributes {} { func.func @main(%arg0: tensor<1x4xf32>) -> tensor<1x3xf32> attributes {} { %0 = stablehlo.constant dense<1.0> : tensor<4x3xf32> %1 = stablehlo.dot_general %arg0, %0, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<1x4xf32>, tensor<4x3xf32>) -> tensor<1x3xf32> return %1 : tensor<1x3xf32> } } )mlir"); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 28 21:41:08 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/legacy_reshape.json
// CHECK: %0 = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32> // CHECK: %1 = "tfl.reshape"(%arg0, %0) : (tensor<1x4xf32>, tensor<2xi32>) -> tensor<2x2xf32> { "version": 3, "operator_codes": [ { "builtin_code": "RESHAPE" } ], "subgraphs": [ { "tensors": [ { "shape": [1, 4],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 986 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/lstm.json
// CHECK-DAG: %[[input_18:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-8.000000e-01, 1.600000e+00]> : tensor<2xf32>}> : (tensor<1x4xf32>) -> tensor<1x4xf32> // CHECK-DAG: %[[input_19:.*]] = "quantfork.stats"({{.*}}) <{layerStats = dense<[-2.000000e+00, 4.000000e+00]> : tensor<2xf32>}> : (tensor<1x2xf32>) -> tensor<1x2xf32> // CHECK: "tfl.unidirectional_sequence_lstm"({{.*}}, %[[input_18]], %[[input_19]], %{{[0-9]+}}, %{{[0-9]+}}, %{{[0-9]+}}, %{{[0-9]+}})
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 06:25:50 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/lower-static-tensor-list.mlir
// CHECK: [[SCALAR_ZERO:%.*]] = arith.constant dense<0> : tensor<i32> // CHECK: [[CONCAT:%.*]] = "tf.Concat"([[SCALAR_ZERO]], [[UNPACK]]#0, [[UNPACK]]#1, [[UNPACK]]#2) : (tensor<i32>, tensor<2x2xf32>, tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<?x2xf32> // CHECK: [[LENGTHS:%.*]] = arith.constant dense<0> : tensor<0xi64>
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/legalize-tf.mlir
} func.func @mean(%arg0: tensor<2x2xf32>, %arg1: tensor<1xi32>) -> tensor<1x2xf32> { %0 = "tf.Mean"(%arg0, %arg1) : (tensor<2x2xf32>, tensor<1xi32>) -> tensor<1x2xf32> func.return %0 : tensor<1x2xf32> // CHECK-LABEL: mean // CHECK: "tfl.mean"(%arg0, %arg1) <{keep_dims = false}> : (tensor<2x2xf32>, tensor<1xi32>) -> tensor<1x2xf32> } func.func @mean_true(%arg0: tensor<2x2xf32>, %arg1: tensor<1xi32>) -> tensor<1x2xf32> {
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/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: return %[[VAL_3]] : tensor<3x6xf32> // CHECK: } func.func @concat_v2_1d_axis(%arg0: tensor<3x3xf32>, %arg1: tensor<3x3xf32>) -> tensor<3x6xf32> { %2 = "mhlo.concatenate"(%arg0, %arg1) <{dimension = 1 : i64}> : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<3x6xf32> func.return %2 : tensor<3x6xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0)