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tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions.mlir
// CHECK-DAG: {{\[\[\[}}-87, -42] // CHECK: %[[quantize:.*]] = "tf.PartitionedCall"(%arg0, %[[in_scale]], %[[in_zp]]) // CHECK-SAME: f = @quantize_i8 // CHECK: %[[conv_quant:.*]] = "tf.PartitionedCall"(%[[quantize]], %[[w_quant]], %[[b_quant]], // CHECK-SAME: %[[in_scale]], %[[in_zp]], %[[w_scale]], %[[w_zp]], // CHECK-SAME: %[[b_scale]], %[[w_zp]], %[[out_scale]], %[[out_zp]]) // CHECK-SAME: f = @quantized_conv2d_with_bias_and_relu6_fn_0
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 01:23:21 UTC 2023 - 15.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.cc
// TFR_ConstantTensorOp ( // ConstantOp (ConstAttr<F32Attr (in_scale[0] * in_scale[1] / // out_scale)) // ) // Currently, all decompositions using this pattern (Conv2D, FC) have the // following preconditions: // * out_scale: float scalar attribute // * in_scale[0] (input scale): float scalar, given by tf.Const -> tfr.cast // * in_scale[1] (filter scale): float scalar/vector
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Nov 21 16:55:41 UTC 2023 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composit_functions_debugging.mlir
// XLA-DAG: %[[conv1_dequantized:.*]] = "tf.PartitionedCall"(%[[conv0_quantized]], %[[w1_quantized]], %[[b1_quantized]], %[[mid_scale]], %[[in_out_zp]], %[[w1_scale]], %[[w_b_zp]], %[[b1_scale]], %[[w_b_zp]], %[[out_scale]],...
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/quantize_composite_functions_xla.mlir
// CHECK-DAG: %[[w0_quantized:.*]] = "tf.Const"() <{value = dense<{{\[\[\[\[}}-42, 18 // CHECK-DAG: %[[in_scale:.*]] = "tf.Const"() <{value = dense<0.0039215642> : tensor<f32>}> : () -> tensor<f32> // CHECK-DAG: %[[in_out_zp:.*]] = "tf.Const"() <{value = dense<-128> : tensor<i32>}> : () -> tensor<i32> // CHECK-DAG: %[[w0_scale:.*]] = "tf.Const"() <{value = dense<0.0150353173> : tensor<f32>}> : () -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 25.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/nms_utils.cc
failed(AddFloatAttr(func, attrs, "nms_iou_threshold", &fbb)) || failed(AddFloatAttr(func, attrs, "y_scale", &fbb)) || failed(AddFloatAttr(func, attrs, "x_scale", &fbb)) || failed(AddFloatAttr(func, attrs, "h_scale", &fbb)) || failed(AddFloatAttr(func, attrs, "w_scale", &fbb))) return failure(); auto use_regular_nms = mlir::dyn_cast_or_null<BoolAttr>(attrs.get("use_regular_nms"));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.h
std::vector<int64_t> in_shape{input_type.getShape().vec()}; std::vector<int64_t> out_shape{output_type.getShape().vec()}; // If the reshape changes the number of dimensions so it cannot be interpreted // as a transpose. if (in_shape.size() != out_shape.size()) { return false; } in_shape.erase(std::remove(in_shape.begin(), in_shape.end(), 1), in_shape.end());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
staging/src/k8s.io/apimachinery/pkg/api/resource/amount.go
// Scale is used for getting and setting the base-10 scaled value. // Base-2 scales are omitted for mathematical simplicity. // See Quantity.ScaledValue for more details. type Scale int32 // infScale adapts a Scale value to an inf.Scale value. func (s Scale) infScale() inf.Scale { return inf.Scale(-s) // inf.Scale is upside-down } const ( Nano Scale = -9 Micro Scale = -6 Milli Scale = -3 Kilo Scale = 3 Mega Scale = 6
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Fri Oct 13 19:42:28 UTC 2023 - 9.3K bytes - Viewed (0) -
docs/pt/docs/tutorial/index.md
Usá-lo em seu editor é o que realmente te mostra os benefícios do FastAPI, ver quão pouco código você tem que escrever, todas as conferências de tipo, auto completações etc. --- ## Instale o FastAPI O primeiro passo é instalar o FastAPI. Para o tutorial, você deve querer instalá-lo com todas as dependências e recursos opicionais. <div class="termy"> ```console $ pip install "fastapi[all]"
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 2.8K bytes - Viewed (0) -
docs/pt/docs/tutorial/request-forms-and-files.md
# Formulários e Arquivos da Requisição Você pode definir arquivos e campos de formulário ao mesmo tempo usando `File` e `Form`. !!! info "Informação" Para receber arquivos carregados e/ou dados de formulário, primeiro instale <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a>. Por exemplo: `pip install python-multipart`. ## Importe `File` e `Form` ```Python hl_lines="1"
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Wed Mar 13 19:02:19 UTC 2024 - 1.4K bytes - Viewed (0)