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Results 1 - 10 of 24 for SQUEEZE (0.11 sec)
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tensorflow/compiler/mlir/lite/transforms/dilated_conv.h
// extra ops are used, so we detect the following patterns: // // // SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> BatchToSpaceND -> BiasAdd // // SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> Pad -> BatchToSpaceND -> // BiasAdd // // SpaceToBatchND -> Expand -> Conv2D -> Squeeze -> BiasAdd -> BatchToSpaceND // // SpaceToBatchND -> Conv2D -> Pad -> BatchToSpaceND -> BiasAdd //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 20K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
int num_cols = tensorType.getShape()[rank - 1]; std::vector<Value> sliced; if (batch_size == 1) { // Batch size is 1, no splitting is required // Squeeze the batch dimension, i.e. reshape // [1, num_rows, num_cols] -> [num_rows, num_cols] auto reshape_op = createReshapeOp(value, {num_rows, num_cols}, element_type, loc, rewriter);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
%0 = "tfl.squeeze"(%arg0) : (tensor<?x?xf32>) -> tensor<?x?xf32> // CHECK: return %arg0 func.return %0 : tensor<?x?xf32> } // ----- // CHECK-LABEL: @squeeze_folder func.func @squeeze_folder(%arg0 : tensor<?x?xf32>) -> tensor<*xf32> { %0 = "tfl.squeeze"(%arg0) : (tensor<?x?xf32>) -> tensor<*xf32> // CHECK: "tfl.squeeze" func.return %0 : tensor<*xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
src/runtime/map_fast64.go
continue } // Only clear key if there are pointers in it. if t.Key.Pointers() { if goarch.PtrSize == 8 { *(*unsafe.Pointer)(k) = nil } else { // There are three ways to squeeze at one or more 32 bit pointers into 64 bits. // Just call memclrHasPointers instead of trying to handle all cases here. memclrHasPointers(k, 8) } }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu May 23 01:17:26 UTC 2024 - 14.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
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/legalize-tf.mlir
%0 = "tf.Squeeze"(%arg0) : (tensor<1x2x2xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32> // CHECK-LABEL:squeezeDefault // CHECK: "tfl.squeeze"(%arg0) <{squeeze_dims = []}> : (tensor<1x2x2xf32>) -> tensor<2x2xf32> } func.func @squeezeSingleAxis(%arg0: tensor<2x1x2xf32>) -> tensor<2x2xf32> { %0 = "tf.Squeeze"(%arg0) {squeeze_dims = [1]} : (tensor<2x1x2xf32>) -> tensor<2x2xf32>
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/tfrt/tests/mlrt/while_to_map_fn.mlir
%outputs_20 = "tf.ResizeBilinear"(%outputs_18, %outputs) {align_corners = false, device = "", half_pixel_centers = false} : (tensor<1x?x?x3xui8>, tensor<2xi32>) -> tensor<1x224x224x3xf32> %outputs_22 = "tf.Squeeze"(%outputs_20) {device = "", squeeze_dims = [0]} : (tensor<1x224x224x3xf32>) -> tensor<224x224x3xf32> %outputs_24 = "tf.Cast"(%outputs_22) {Truncate = false, device = ""} : (tensor<224x224x3xf32>) -> tensor<224x224x3xui8>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 06:40:22 UTC 2024 - 68.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/fuse-tftext.mlir
%267 = "tf.Reshape"(%266, %5) {device = ""} : (tensor<?x?xi1>, tensor<1xi32>) -> tensor<?xi1> %268 = "tf.Where"(%267) {device = ""} : (tensor<?xi1>) -> tensor<?x1xi64> %269 = "tf.Squeeze"(%268) {device = "", squeeze_dims = [1]} : (tensor<?x1xi64>) -> tensor<?xi64> %270 = "tf.GatherV2"(%264, %269, %14) {batch_dims = 0 : i64, device = ""} : (tensor<?xi64>, tensor<?xi64>, tensor<i32>) -> tensor<?xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 460.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
auto float_graph = readonly_model_->subgraphs()->Get(0); // The original model reshape->custom->custom->squeeze. ASSERT_THAT(*float_graph->operators(), SizeIs(4)); // The resulting model should be: // reshape->dequantize->custom->custom->quantize->squeeze. ASSERT_THAT(subgraph->operators, SizeIs(6)); const std::vector<BuiltinOperator> op_codes = {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
func.func @PadStridedSliceNewAxisMask2(%arg0: tensor<4x64x64x1xf32>) -> tensor<1x4x64x64xf32> { %cst = arith.constant dense<0> : tensor<3xi32> %cst_0 = arith.constant dense<1> : tensor<3xi32> %0 = "tf.Squeeze"(%arg0) {T = f32, _output_shapes = ["tfshape$dim { size: 4 } dim { size: 64 } dim { size: 64 }"], device = "", squeeze_dims = []} : (tensor<4x64x64x1xf32>) -> tensor<4x64x64xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0)