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Results 1 - 10 of 113 for matmult (0.13 sec)
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tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass_test.cc
// done in parallel. // // This graph is: // (Const0, Const0) -> MatMul0 // (Const1, Const1) -> MatMul1 // (MatMul0, MatMul1) -> MatMulCombined // // Device0: [Const0, Const0, MatMul0] // Device1: [Const1, Const1, MatMul1, MatMulCombined] // // Cluster0: [Const0, Const0, MatMul0] // Cluster1: [Const1, Const1, MatMul1] // Cluster2: [MatMulCombined]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 10:11:10 UTC 2024 - 79.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composit_functions_debugging.mlir
// TF-DAG: %[[pc_3:.*]] = "tf.PartitionedCall"(%arg0, %[[cst_1]]) <{config = "", config_proto = "", executor_type = "", f = @composite_matmul_fn_2_0}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 01:23:21 UTC 2023 - 80.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op.mlir
// WholeModel-DAG: "tf.DumpTensor"(%[[m1]]) <{enabled = true, file_name = "unquantized_tensor_data.pb", func_name = "matmul2", log_dir_path = "/tmp/dumps/composite_matmul_fn_1", node_name = "MatMul_1"} // WholeModel-DAG: return %[[m1]] // IntPerLayer-LABEL: func @matmul2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 37.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc
std::vector<Value> sliced_rhs = sliceInput(input_rhs, bcast.y_batch_size(), loc, rewriter); // Compute (single batch) MatMul for each output batch. std::vector<Value> matmuls; matmuls.reserve(bcast.output_batch_size()); for (int batch_idx : llvm::seq<int>(0, bcast.output_batch_size())) { int lhs_batch_idx, rhs_batch_idx; if (bcast.IsBroadcastingRequired()) {
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/quantization/tensorflow/tests/quantize_weights.mlir
// CHECK: %[[MATMUL_3:.*]] = "tf.MatMul"(%arg0, %[[ORIGINAL_IDENTITY]]) <{transpose_a = false, transpose_b = false}> {attr_map = "0:transpose_a,1:transpose_a", device = ""} : (tensor<1x2x2x2xf32>, tensor<2x1024xf32>) -> tensor<*xf32> // CHECK: return %[[MATMUL_1]], %[[MATMUL_2]], %[[MATMUL_3]] : tensor<*xf32>, tensor<*xf32>, tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 42K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test.cc
TFE_TensorHandle* m2 = DoubleTestMatrixTensorHandle3X2(ctx); TFE_Op* matmul = MatMulOp(ctx, m1, m2); TFE_OpSetDevice(matmul, "/job:localhost/replica:0/task:0/device:CPU:0", status); ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_Op* matmul2 = MatMulOp(ctx, m1, m1); TFE_OpSetDevice(matmul2, "/job:localhost/replica:0/task:0/device:CPU:0", status);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 03 20:50:20 UTC 2023 - 94.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/fused_kernel_matcher.cc
if ((matmul->hasAttr("grad_a") && mlir::cast<BoolAttr>(matmul->getAttr("grad_a")).getValue()) || (matmul->hasAttr("grad_b") && mlir::cast<BoolAttr>(matmul->getAttr("grad_b")).getValue())) { (void)rewriter.notifyMatchFailure(matmul, [&](Diagnostic &diag) { diag << "FusedMatMul kernel does not support grad_a/grad_b attrs"; }); return false; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 14.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/matmul.mlir
Christian Sigg <******@****.***> 1714640622 -0700
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/include_variables_in_init_v1.py
# CHECK-NEXT: %[[READ_VAR_0:.*]] = "tf.ReadVariableOp"(%[[ARG_2]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: %[[MATMUL_0:.*]] = "tf.MatMul"(%[[ARG_1]], %[[READ_VAR_0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return %[[MATMUL_0]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]]) y = tf.compat.v1.get_variable( name='y',
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 3.7K bytes - Viewed (0)