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Results 1 - 10 of 14 for SQUARED_DIFFERENCE (0.27 sec)
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tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/input_arrays.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 867 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/math.mlir
// Confirm that attributes that cannot be stored in the flatbuffer options // for a given operator are dropped silently. %1 = "tfl.squared_difference"(%arg0, %0) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("squared_difference") %2 = "tfl.mul"(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> loc("mul")
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/device-transform-nnapi.mlir
// RUN: tac-translate -input-mlir -output-mlir -device-specs=NNAPI %s -o - 2>&1 | FileCheck %s 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/lite/experimental/tac/tests/device-transform-gpu.mlir
func.return %0 : tensor<*xf32> } // CHECK-NOT: "tfl.reshape" // CHECK: "tfl.pack" // ----- func.func @squaredDifference(%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: func @squaredDifference(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.cc
pack_out_shape, &rewriter); // Rewire output & get rid of the pack op. rewriter.replaceOp(pack_op, reshape_op.getResult()); return success(); } // ================== squared_difference ======================== LogicalResult SquaredDifference::matchAndRewrite( TFL::SquaredDifferenceOp squared_diff_op, PatternRewriter& rewriter) const { auto x = squared_diff_op.getLhs();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 25.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
REDUCE_MIN = 89, FLOOR_DIV = 90, REDUCE_ANY = 91, SQUARE = 92, ZEROS_LIKE = 93, FILL = 94, FLOOR_MOD = 95, RANGE = 96, RESIZE_NEAREST_NEIGHBOR = 97, LEAKY_RELU = 98, SQUARED_DIFFERENCE = 99, MIRROR_PAD = 100, ABS = 101, SPLIT_V = 102, UNIQUE = 103, CEIL = 104, REVERSE_V2 = 105, ADD_N = 106, GATHER_ND = 107, COS = 108, WHERE = 109, RANK = 110,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
REDUCE_MIN = 89, FLOOR_DIV = 90, REDUCE_ANY = 91, SQUARE = 92, ZEROS_LIKE = 93, FILL = 94, FLOOR_MOD = 95, RANGE = 96, RESIZE_NEAREST_NEIGHBOR = 97, LEAKY_RELU = 98, SQUARED_DIFFERENCE = 99, MIRROR_PAD = 100, ABS = 101, SPLIT_V = 102, UNIQUE = 103, CEIL = 104, REVERSE_V2 = 105, ADD_N = 106, GATHER_ND = 107, COS = 108, WHERE = 109, RANK = 110,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
// In above calculation, they are replaced by new values. These new mean and // variance are calculated as following: // new_mean = mean(x, axis=[0, 1, 2]) // new_variance = mean(squared_difference(x, new_mean), axis=[0, 1, 2]) // // The DDR rule for the is_training equals true case is as following: // def : Pattern< // (TF_FusedBatchNormV3Op:$root // $x, $scale, $offset, $mean, $variance,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 64.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%0 = "tfl.squared_difference"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32> %1 = "tfl.relu"(%0) : (tensor<1xf32>) -> tensor<1xf32> func.return %1: tensor<1xf32> // CHECK-LABEL: squaredDifferenceReluRemoveRelu // CHECK: %[[RESULT:.*]] = tfl.squared_difference %arg0, %arg1 : tensor<1xf32> // CHECK: return %[[RESULT]] }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
%1 = "tf.Relu6"(%0) : (tensor<1xf32>) -> tensor<1xf32> func.return %1: tensor<1xf32> // CHECK-LABEL: squaredDifferenceRelu // CHECK: tfl.squared_difference %arg0, %arg1 : tensor<1xf32> // CHECK: %1 = "tfl.relu6"(%0) : (tensor<1xf32>) -> tensor<1xf32> // CHECK: return } func.func @maxPool2D(%arg0: tensor<1x1x1x16xf32>) -> tensor<1x1x1x16xf32> { // OK
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0)