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Results 11 - 20 of 58 for mat_mul (0.23 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions.mlir
// CHECK-LABEL: private @composite_matmul_with_bias_and_relu6_fn_1 // CHECK-NEXT: %[[matmul:.*]] = "tf.MatMul"(%arg0, %arg1) // CHECK-SAME: attr_map = "0:transpose_a,1:transpose_b" // CHECK-NEXT: tf.BiasAdd // CHECK-NEXT: tf.Relu6 // CHECK-NEXT: return // CHECK-LABEL: private @composite_matmul_with_bias_and_relu_fn_1 // CHECK-NEXT: tf.MatMul"(%arg0, %arg1) // CHECK-SAME: attr_map = "0:transpose_a,1:transpose_b"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/sink_variable_as_named_array.mlir
// CHECK: "tf.VarHandleOp" // CHECK-NOT: [[VARIABLE:%.*]] = "tf.ReadVariableOp" // CHECK-NEXT: [[KEY:%.*]], [[FUTURE:%.*]] = "tf.IfrtLoadVariable" // CHECK-SAME: used_by_host = true // CHECK-NEXT: [[MATRES:%.*]] = "tf.MatMul"(%arg0, [[FUTURE]]) // CHECK-NEXT: [[RES:%.*]] = "tf.IfrtCall"(%arg0, [[KEY]]) <{program_id = 6515870160938153680 : i64, variable_arg_indices = [1 : i32]}> // CHECK-NEXT: return [[RES]], [[MATRES]] : tensor<1x1xf32>, tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 15:33:17 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
(TF_SubOp $beta, (TF_MulOp $m, $mul)))>; class TFi32<int v> : ConstantAttr<I32ElementsAttr, !cast<string>(v)>; // Matmul without transpose on b to matmul with explicit transpose op and // transposed b. def ConvertMatmulWithoutTransposeToWithTranspose : Pat<(TF_MatMulOp $a, $b, ConstBoolAttrFalse:$at, ConstBoolAttrFalse, $grad_a, $grad_b),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
] ) def matmul(self, matmul_input: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Args: matmul_input: Input tensor to matmul with the filter. Returns: A map of: output key -> output result. """ out = math_ops.matmul(matmul_input, self.matmul_filters) return {'output': out}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
).astype(np.float32) class TwoMatmulModel(module.Module): """A model with two matmul ops.""" @def_function.function def matmul(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Args: input_tensor: Input tensor to matmul with the filter. Returns: A 'output' -> output tensor mapping """
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/device_conversion.mlir
%arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]}) -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) { // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0" %2 = "tf.MatMul"(%arg0, %arg1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:GPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 645 bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/attributes.mlir
// CHECK: {{%.*}} = tfrt_fallback_async.executeop {{.*}} device("/device:CPU:0") "tf.MatMul" // CHECK-SAME: {T = f32, transpose_a = false, transpose_b = false}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/basic.mlir
// CHECK-NEXT: [[ch1:%.*]], [[var:%.*]] = tfrt_fallback_async.executeop.seq([[in_chain]]) {{.*}} "tf.ReadVariableOp"([[arg1]]) // CHECK-NEXT: [[r0:%.*]] = tfrt_fallback_async.executeop {{.*}} "tf.MatMul"([[arg0]], [[var]]) %2 = "tf.MatMul"(%arg0, %1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
// CHECK: %[[TRANSPOSE:.*]] = "tf.Transpose"(%[[DEQUANT]], %[[CST]]) : (tensor<3x4xf32>, tensor<?xi32>) -> tensor<*xf32> // CHECK: %[[MATMUL:.*]] = "tf.MatMul"(%arg0, %[[TRANSPOSE]]) <{grad_a = false, grad_b = false, transpose_a = false, transpose_b = true}> : (tensor<2x3xf32>, tensor<*xf32>) -> tensor<2x4xf32> // CHECK: return %[[MATMUL]] : tensor<2x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.cc
auto matmul = rewriter.create<TFL::BatchMatMulOp>( loc, RankedTensorType::get(matmul_shape, result_type.getElementType()), lhs_flattend, rhs_flattend, /*adj_x*/ false_attr, /*adj_y*/ false_attr, /*asym_quant_input*/ false_attr); if (result_type.hasStaticShape()) { auto reshaped = rewriter.create<mhlo::ReshapeOp>(loc, result_type, matmul.getResult()); return reshaped.getResult();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 19.2K bytes - Viewed (0)