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Results 81 - 90 of 92 for 9xf32 (0.04 sec)
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tensorflow/compiler/mlir/tfr/tests/ops.mlir
func.return %0 : tensor<?xi32> } // ----- func.func @constant_tensor_invalid_2(%arg0: vector<1xi32>) -> tensor<1xf32> { // expected-error@+1 {{input and output should have same shape and element type}} %0 = "tfr.constant_tensor"(%arg0) : (vector<1xi32>) -> tensor<1xf32> func.return %0 : tensor<1xf32> } // ----- func.func @constant_tensor_invalid_3(%arg0: vector<1xi32>) -> tensor<1x1xi32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jan 14 22:15:06 UTC 2023 - 13.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
func.func @add_with_activation_transpose_broadcasted_rhs(%arg0: tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<4xf32> %1 = stablehlo.broadcast_in_dim %0, dims = [1] : (tensor<4xf32>) -> tensor<1x4x3x3xf32> %2 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> %3 = stablehlo.add %2, %1 : tensor<1x4x3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_weights.mlir
%2 = "tf.MatMul"(%arg2, %arg1) {} : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> %3 = "tf.AddV2" (%arg1, %arg1) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> %4 = "tf.Identity"(%1) {device = ""} : (tensor<i32>) -> tensor<i32> %5 = "tf.Identity"(%3) {device = ""} : (tensor<*xf32>) -> tensor<*xf32> %6 = "tf.Identity"(%2) {device = ""} : (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/compiler/mlir/quantization/stablehlo/tests/bridge/optimize.mlir
} // ----- // CHECK-LABEL: func @convolution_add_add_f32 func.func @convolution_add_add_f32( %lhs: tensor<?x3x2x1xf32>, %rhs: tensor<2x1x1x1xf32>, %zp_offset: tensor<?x2x2x1xf32>, %bias: tensor<1xf32> ) -> tensor<?x2x2x1xf32> { // CHECK-DAG: %[[conv:.*]] = mhlo.convolution // CHECK-DAG: %[[combined:.*]] = chlo.broadcast_add %[[conv:.*]], %[[zp_offset:.*]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 24 02:26:47 UTC 2024 - 10.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize-dynamic-range.mlir
// CHECK-LABEL: QuantizeCustomOp // CustomOp-LABEL: QuantizeCustomOp func.func @QuantizeCustomOp(%arg0: tensor<1x1x1x1xf32>) -> (tensor<*xf32>, tensor<*xf32>, tensor<*xf32>) attributes {tf.entry_function = {inputs = "input", outputs = "custom_op"}} { %0 = "quantfork.stats"(%arg0) {layerStats = dense<[0.000000e+00, 2.550000e+02]> : tensor<2xf32>} : (tensor<1x1x1x1xf32>) -> tensor<1x1x1x1xf32> %w_1 = arith.constant dense<127.0> : tensor<4096x1x1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_weight_param.mlir
func.func @no_qdq_for_non_weight_constant(%arg0: tensor<1x2xf32>, %arg1: tensor<2x3xf32>) -> tensor<1x3xf32> attributes {tf._original_func_name = "main_0"} { %cst = "tf.Const"() {value = dense<4.000000e-02> : tensor<3xf32>} : () -> tensor<3xf32> %0 = "tf.XlaCallModule"(%arg0, %arg1, %cst) { Sout = [#tf_type.shape<1x3>], _entry_function = @composite_dot_general_with_bias_fn, _original_entry_function = "composite_dot_general_with_bias_fn",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/stack_ops_decomposition.mlir
// CHECK-NEXT: %[[UPDATE_SLICE:.*]] = "tf.Reshape"(%[[PUSHVAL]], %[[UPDATE_SHAPE]]) : (tensor<f32>, tensor<1xi32>) -> tensor<1xf32> // CHECK-NEXT: %[[UPDATE:.*]] = "tf.XlaDynamicUpdateSlice"(%[[READ_VAL]], %[[UPDATE_SLICE]], %[[READ_SIZE]]) : (tensor<10xf32>, tensor<1xf32>, tensor<1xi32>) -> tensor<10xf32> // CHECK-NEXT: "tf.AssignVariableOp"(%[[BUFFER]], %[[UPDATE]]) : (tensor<!tf_type.resource<tensor<10xf32>>>, tensor<10xf32>) -> ()
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 25.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.td
tensor type, the shape shouldn't be changed during the conversion. Example: ```mlir %1 = tfr.constant_tensor(%0) : f32 -> tensor<f32> %3 = tfr.constant_tensor(%2) : vector<1xf32> -> tensor<1xf32> ``` }]; let arguments = (ins TFR_AllAttrTypes:$arg); let results = (outs TFR_singleTensorType:$out); let hasCanonicalizer = 1; let hasVerifier = 1; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 10:54:29 UTC 2024 - 17.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range.mlir
// CustomOpNotWeightOnly-LABEL: QuantizeCustomOp func.func @QuantizeCustomOp(%arg0: tensor<1x1x1x1xf32>) -> tensor<*xf32> attributes {tf.entry_function = {inputs = "input", outputs = "custom_op"}} { %0 = "quantfork.stats"(%arg0) {layerStats = dense<[0.000000e+00, 2.550000e+02]> : tensor<2xf32>} : (tensor<1x1x1x1xf32>) -> tensor<1x1x1x1xf32> %w = arith.constant dense<127.0> : tensor<1024x1x1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 23 21:09:00 UTC 2024 - 23.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_op_base.td
// (i.e., after converting reference types to their corresponding TensorFlow or // standard types). Also, this allows compatible types so it is legal to have // tensor<*xf32> and tensor<4xf32> types. def TF_SameOperandsAndResultTypeResolveRef : TraitList< InferTensorType.traits # [ NativeOpTrait<"TF::SameOperandsAndResultTypeResolveRef"> ]>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 30.5K bytes - Viewed (0)