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Results 11 - 17 of 17 for 8x8x8x3xf32 (0.19 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
} func.func @fakeQuantArgsTrue(%arg0: tensor<8x8x8x8xf32>) -> tensor<8x8x8x8xf32> { %0 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {min = -0.1 : f32, max = 0.2 : f32, num_bits = 5, narrow_range = true} : (tensor<8x8x8x8xf32>) -> tensor<8x8x8x8xf32> func.return %0 : tensor<8x8x8x8xf32> // CHECK-LABEL: fakeQuantArgsTrue
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/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
%0 = stablehlo.constant() {value = dense<7.000000e+00> : tensor<8x8x3x3xf32>} : () -> tensor<8x8x3x3xf32> %2 = stablehlo.convolution(%arg0, %0) dim_numbers = [b, f, 0, 1]x[o, i, 0, 1]->[b, f, 0, 1], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x8x4x4xf32>, tensor<8x8x3x3xf32>) -> tensor<1x8x4x4xf32> return %2 : tensor<1x8x4x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
func.return %0 : tensor<256x16x32x32xf32> // LAYOUT-LABEL: Conv2dNCHW // LAYOUT: "tfl.conv_2d" } func.func @fusedBatchNormV3(tensor<8x8x8x8xf32>, tensor<8xf32>, tensor<8xf32>, tensor<8xf32>, tensor<8xf32>) -> (tensor<8x8x8x8xf32>, tensor<8xf32>) { ^bb0(%arg0: tensor<8x8x8x8xf32>, %arg1: tensor<8xf32>, %arg2: tensor<8xf32>, %arg3: tensor<8xf32>, %arg4: tensor<8xf32>): // OK
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/tests/prepare-composite-functions-tf.mlir
// CHECK: [[VAL_40:%.*]] = arith.constant dense<0> : tensor<1xi32> // CHECK: [[VAL_41:%.*]] = "tf.ReverseV2"([[VAL_0]], [[VAL_40]]) : (tensor<8x8x8xf32>, tensor<1xi32>) -> tensor<8x8x8xf32> // CHECK: [[VAL_6:%.*]] = arith.constant dense<[1, 0]> : tensor<2xi32> // CHECK: [[VAL_7:%.*]] = "tf.Transpose"([[VAL_3]], [[VAL_6]]) : (tensor<8x40xf32>, tensor<2xi32>) -> tensor<40x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
// permutated to match the new input shape. // CHECK: (tensor<1x16x16x4xf32>, tensor<f32>) -> tensor<1x8x8x4xf32> // Check that a `stablehlo.transpose` is added to the result to match the shape // of the users. // CHECK: %[[TRANSPOSE:.+]] = stablehlo.transpose %[[REDUCE_WINDOW]], dims = [0, 3, 1, 2] : (tensor<1x8x8x4xf32>) -> tensor<1x4x8x8xf32> // CHECK: return %[[TRANSPOSE]] // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/canonicalize.mlir
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/lite/tests/optimize.mlir
// CHECK: %[[RESULT:.*]] = "tfl.reshape"(%arg0, %[[CONST:.*]]) : (tensor<?x1x8x3xf32>, tensor<3xi32>) -> tensor<?x8x3xf32> // CHECK: return %[[RESULT]] } func.func @ConvertSqueezeToReshapeWithDynamicDimension2(%arg0: tensor<?x1x8x3xf32>) -> tensor<1x8x3xf32> { %0 = "tfl.squeeze"(%arg0) {squeeze_dims = [0]}: (tensor<?x1x8x3xf32>) -> tensor<1x8x3xf32> func.return %0: tensor<1x8x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0)