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Results 1 - 10 of 12 for hard_swish (0.46 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
// RUN: odml-to-stablehlo-opt -composite-lowering -verify-diagnostics %s | FileCheck %s func.func @hardswish(%arg0: tensor<2xf32>) -> (tensor<*xf32>) { %0 = mhlo.composite "aten.hardswish.default" %arg0 {decomposition = @XlaCallModule_aten.hardswish.default.impl_0} : (tensor<2xf32>) -> tensor<2xf32> %1 = "tf.Identity"(%0) {device = ""} : (tensor<2xf32>) -> tensor<*xf32> %2 = "tf.Identity"(%1) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/test_schema.fbs
GATHER_ND = 107, COS = 108, WHERE = 109, RANK = 110, ELU = 111, REVERSE_SEQUENCE = 112, MATRIX_DIAG = 113, QUANTIZE = 114, MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 19 19:46:06 UTC 2021 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
GATHER_ND = 107, COS = 108, WHERE = 109, RANK = 110, ELU = 111, REVERSE_SEQUENCE = 112, MATRIX_DIAG = 113, QUANTIZE = 114, MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126,
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
GATHER_ND = 107, COS = 108, WHERE = 109, RANK = 110, ELU = 111, REVERSE_SEQUENCE = 112, MATRIX_DIAG = 113, QUANTIZE = 114, MATRIX_SET_DIAG = 115, ROUND = 116, HARD_SWISH = 117, IF = 118, WHILE = 119, NON_MAX_SUPPRESSION_V4 = 120, NON_MAX_SUPPRESSION_V5 = 121, SCATTER_ND = 122, SELECT_V2 = 123, DENSIFY = 124, SEGMENT_SUM = 125, BATCH_MATMUL = 126,
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/tests/optimize.mlir
%2 = "tfl.mul"(%1, %six) {fused_activation_function = "NONE"} : (tensor<1xf32>, tensor<f32>) -> tensor<1xf32> func.return %2: tensor<1xf32> // CHECK: %0 = "tfl.hard_swish"(%arg0) : (tensor<1xf32>) -> tensor<1xf32> } // CHECK-LABEL: @HardSwishPatternTwo func.func @HardSwishPatternTwo(%arg0: tensor<1x128x128x3xf32>) -> tensor<1x128x128x3xf32> {
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/transforms/optimize_patterns.td
[(HasOneUse $pool_out)]>; } // TODO(hinsu): Also fuse ops corresponding to SIGN_BIT fused // activation functions. // Currently we're not fusing tanh, sigmoid, hard_swish and other activations // those cannot be simply translated into clamping. foreach actFnPair = [[TFL_ReluOp, TFL_AF_Relu], [TFL_Relu6Op, TFL_AF_Relu6],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 66.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
RemoveReshapeBeforeFullyConnected, ConvertTFLBroadcastToMulOp>(ctx); (void)applyPatternsAndFoldGreedily(func, std::move(phase_0_patterns)); // Potentially the binary ops might be fused together, like hard_swish, thus // we explore these potentially first and then fuse the binary ops with the // following ops in a second pattern match. TFL::populateWithGenerated(patterns); patterns
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_lowering_patterns.td
def LegalizeHardSwishComposite: Pat< (MHLO_CompositeOp:$old_val (variadic $input), ConstantStrAttr<StrAttr, "aten.hardswish.default">, $_, $_, $_), (TFL_HardSwishOp $input)>; def IsNchwLayoutOp: Constraint<CPred< "$0.get(\"is_nchw_op\") && $0.get(\"is_nchw_op\").dyn_cast<BoolAttr>() "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
return printOneResultOp(getOperation(), p); } }]; } def TFL_HardSwishOp: TFL_Op<"hard_swish", [ Pure, SameOperandsAndResultShape, QuantizableResult, PredOpTrait<"input and output must have same element type", TFL_TCresVTEtIsSameAsOp<0, 0>>]> { let summary = "Hardswish activation function."; let description = [{ Computes hard-swish activation function
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/hardwares/gpu_hardware.cc
TargetHardwareOpRegistration<GpuHardware, Op> Op##_GpuHardware_hardware( \ Create); // Currently used for these ops: // tfl.Abs / tfl.Average_pool_2d / tfl.Cos / tfl.div / tfl.exp / tfl.hardswish / // tfl.log / tfl.logistic / tfl.max_pool_2d / tfl.mirror_pad / tfl.maximum / // tfl.custom / tfl.mean / tfl.minimum / tfl.pad / tfl.pow / tfl.prelu / // tfl.relu / tfl.relu6 / tfl.rsqrt / tfl.sin / tfl.slice / tfl.softmax /
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 06 03:08:33 UTC 2023 - 7.8K bytes - Viewed (0)