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Results 11 - 20 of 25 for 3x1x1x2xf32 (0.16 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-quant.mlir
} : (tensor<1x6x6x3xf32>, tensor<2x3x3x2x!tf_type.qint8>, tensor<f32>, tensor<i32>) -> tensor<1x4x1x2xf32> func.return %0 : tensor<1x4x1x2xf32> } // ----- // CHECK-LABEL: func @uniform_quantized_convolution_hybrid_same func.func @uniform_quantized_convolution_hybrid_same(%input: tensor<1x2x2x3xf32>) -> tensor<1x2x1x2xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 01:25:29 UTC 2024 - 37.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize-dynamic-range.mlir
%custom_2 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32> %custom_3 = "tfl.custom"(%arg0, %dq_w) {custom_code = "CustomTestOp", custom_option = #tfl<const_bytes : "0x">} : (tensor<1x1x1x1xf32>, tensor<1024x1x1x1xf32>) -> tensor<*xf32>
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/lite/stablehlo/tests/fuse_mhlo_convolution.mlir
// CHECK-DAG: %[[CST:.+]] = mhlo.constant dense<[1.000000e-01, 2.000000e-01]> : tensor<2xf32> // CHECK-DAG: %[[CST_BCAST:.+]] = "mhlo.broadcast_in_dim"(%[[CST]]) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<2xf32>) -> tensor<1x1x3x2xf32> // CHECK-DAG: %[[NEW_FILTER:.+]] = mhlo.multiply %[[CST_BCAST]], %[[FILTER]] : tensor<1x1x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-tf-quantize.mlir
module { func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> { %1 = arith.constant dense<1> : tensor<1xi32> %2 = arith.constant dense<2.0> : tensor<1x1x2xf32> %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""} : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32> func.return %3 : tensor<2x1x2xf32> } } //CHECK: module {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir
} // ----- // CHECK-LABEL: testSliceConcat func.func @testSliceConcat(%arg0: tensor<3x1x512xf32>) -> tensor<3x1x512xf32> { %0 = "mhlo.slice"(%arg0) <{limit_indices = dense<[1, 1, 512]> : tensor<3xi64>, start_indices = dense<[0, 0, 0]> : tensor<3xi64>, strides = dense<1> : tensor<3xi64>}> : (tensor<3x1x512xf32>) -> tensor<1x1x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-numeric-verify.mlir
%8 = "quantfork.stats"(%7) { layerStats = dense<[0.0, 1.4]> : tensor<2xf32> } : (tensor<?x1x1x3xf32>) -> tensor<?x1x1x3xf32> %9 = tfl.mul %8, %4 {fused_activation_function = "NONE"} : tensor<?x1x1x3xf32> %10 = "quantfork.stats"(%9) { layerStats = dense<[0.000000e+00, 5.6]> : tensor<2xf32> } : (tensor<?x1x1x3xf32>) -> tensor<?x1x1x3xf32> func.return %10 : tensor<?x1x1x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-dynamic-range.mlir
// MinElement-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 - 38.2K 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/lite/tests/optimize.mlir
// CHECK-LABEL: squeezeToReshape func.func @squeezeToReshape(%arg0: tensor<1x1x2xf32>) -> tensor<2xf32> { %0 = "tfl.squeeze"(%arg0) : (tensor<1x1x2xf32>) -> tensor<2xf32> func.return %0 : tensor<2xf32> // CHECK-DAG: [[CONST:.*]] = arith.constant dense<2> : tensor<1xi32> // CHECK: %[[RESULT:.*]] = "tfl.reshape"(%arg0, %[[CONST:.*]]) : (tensor<1x1x2xf32>, tensor<1xi32>) -> tensor<2xf32> // CHECK: return %[[RESULT]] }
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/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
// {0}, then it returns: tensor<1x3x5xi32>. // * If `xla_gather_op_output_type` == tensor<3x5xf32> and `collapsed_dims` == // {1, 3}, then it returns: tensor<3x1x5x1xf32>. Type GetSliceOpOutputType(Type xla_gather_op_output_type, const absl::flat_hash_set<int64_t>& collapsed_dims) { if (auto ranked_output_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0)