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Results 21 - 30 of 163 for matmult (0.69 sec)
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tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
bias_grad = tf.reshape(updates_grad_reshaped, input_value_shape) a = math_ops.conj(op.inputs[0]) b = math_ops.conj(op.inputs[1]) grad_a = gen_math_ops.mat_mul(grad, b) grad_b = gen_math_ops.mat_mul(grad, a, transpose_a=True) return [grad_a, grad_b, bias_grad] @Composite( 'NewMaxPool', inputs=['input_: T'], attrs=[
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 31 20:23:51 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.td
(IsInt8ElementType $weight), (IsConstTensor $weight), (IsInt32ElementType $matmul), (HasStaticShapeConstraint $weight)], [], (addBenefit 10)>; // Convert Matmul with hybrid inputs (f32 activation/int8 weight) to XlaDotV2 def ConvertTFMatMulToXLADotV2OpWeightOnly : Pat< (TF_MatMulOp:$matmul $input, (TF_MulOp (TF_CastOp (TF_IdentityOp $weight), $truncate1), $scale),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Dec 10 05:52:02 UTC 2023 - 21.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/back2back_fake_quant.pbtxt
input: "sequential/quant_dense/MatMul/kquant/FakeQuantWithMinMaxVars/ReadVariableOp" input: "sequential/quant_dense/MatMul/kquant/FakeQuantWithMinMaxVars/ReadVariableOp_1" attr { key: "narrow_range" value { b: false } } attr { key: "num_bits" value { i: 8 } } } node { name: "sequential/quant_dense/MatMul/kquant/IdentityN"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 15 19:42:47 UTC 2021 - 25.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/multi_arguments_results_v1.py
# CHECK-DAG: %[[MUL1:.*]] = "tf.MatMul"(%[[ARG0]], %[[ARG1]]) # CHECK-DAG: %[[MUL2:.*]] = "tf.MatMul"(%[[ARG1]], %[[ARG0]]) # CHECK: %[[IDENTITY:.*]]:2 = "tf.IdentityN"(%[[MUL1]], %[[MUL2]]) # CHECK: return %[[IDENTITY]]#1, %[[IDENTITY]]#0 def Test(): x = tf.constant(1.0, shape=(5, 3)) y = tf.constant(1.0, shape=(3, 5)) s = tf.matmul(x, y) t = tf.matmul(y, x) [t, s] = array_ops.identity_n([t, s])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 3.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/control_flow_v1.pbtxt
op: "Identity" input: "Placeholder_1" attr { key: "T" value { type: DT_BOOL } } } node { name: "cond/MatMul" op: "MatMul" input: "cond/MatMul/Switch:1" input: "cond/MatMul/Switch_1:1" attr { key: "T" value { type: DT_FLOAT } } attr { key: "transpose_a" value { b: false }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 23 21:23:31 UTC 2020 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/merge_duplicate_resource_ops.mlir
%outputs_7, %control_8 = tf_executor.island wraps "tf.Const"() {value = dense<"MatMul/b_0"> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string> %outputs_9, %control_10 = tf_executor.island wraps "tf.VarHandleOp"() {container = "", shared_name = "MatMul/b_0"} : () -> tensor<!tf_type.resource<tensor<20x4096xf32>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 26 04:26:16 UTC 2023 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/unroll_batch_matmul_disabled.pbtxt
# RUN: tf_tfl_translate -unfold_batchmatmul=false -tf-input-arrays=Placeholder,Placeholder_1 -tf-input-shapes=2,5,3:3,7 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-output-arrays=MatMul -output-mlir %s -o - 2>&1 | FileCheck %s node { name: "Placeholder" op: "Placeholder" attr { key: "dtype" value { type: DT_FLOAT } } attr { key: "shape" value { shape { dim { size: 2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/opens2s_gnmt_mixed_precision.golden_summary
Transpose 2 Unpack 1 cluster 2 size 44 Cast 2 ConcatV2 2 Const 18 ExpandDims 1 GatherV2 2 Less 1 MatMul 1 Mul 1 Pack 1 Prod 2 Range 1 Reshape 3 Shape 8 StridedSlice 1 cluster 3 size 10 AddN 1 Const 1 MatMul 2 Mul 1 Reshape 3 Sum 1 Transpose 1 cluster 4 size 11 ConcatOffset 1 Const 4 ReverseSequence 1 Slice 2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 5K bytes - Viewed (0) -
tensorflow/c/eager/c_api_distributed_test.cc
ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_Op* matmul = MatMulOp(ctx, h0_task1, h1_task1); TFE_OpSetDevice(matmul, remote_device_name, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_TensorHandle* retvals[1]; int num_retvals = 1; TFE_Execute(matmul, &retvals[0], &num_retvals, status); EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
} return ConstantFoldOpIfPossible(value.getDefiningOp()).front(); } // Matches convolution op with "NHWC" data format or matmul op with false adj_y. // The list of supported ops in this function is: // - Conv2DOp // - Conv3DOp // - DepthwiseConv2dNativeOp // - MatMulOp // - BatchMatMulV2Op LogicalResult MatchSupportedAffineOp(Operation* op, Value& binding_output,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0)