[FX] disable 2 of conv3d and type_as tests (#1224)

* Update test_convolution.py

* Update test_type_as.py

* Update config.yml

* Update test_convolution.py

* c++ format fix

* manual fix format for one file

.circleci/config.yml

@@ -747,7 +747,7 @@ parameters:
   # Nightly platform config
   torch-nightly-build:
     type: string
-    default: "1.13.0.dev20220715+cu113"
+    default: "1.13.0.dev20220731+cu113"
   torch-nightly-build-index:
     type: string
     default: "https://download.pytorch.org/whl/nightly/cu113"

core/conversion/conversionctx/ConversionCtx.cpp

@@ -107,7 +107,7 @@ ConversionCtx::ConversionCtx(BuilderSettings build_settings)
   }
 
   cfg->setAvgTimingIterations(settings.num_avg_timing_iters);
-  if (settings.workspace_size != 0){
+  if (settings.workspace_size != 0) {
     cfg->setMemoryPoolLimit(nvinfer1::MemoryPoolType::kWORKSPACE, settings.workspace_size);
   }
 
@@ -124,13 +124,13 @@ ConversionCtx::ConversionCtx(BuilderSettings build_settings)
         settings.enabled_precisions.find(nvinfer1::DataType::kFLOAT) == settings.enabled_precisions.end(),
         "DLA supports only fp16 or int8 precision");
     cfg->setDLACore(settings.device.dla_core);
-    if (settings.dla_sram_size != 1048576){
+    if (settings.dla_sram_size != 1048576) {
       cfg->setMemoryPoolLimit(nvinfer1::MemoryPoolType::kDLA_MANAGED_SRAM, settings.dla_sram_size);
     }
-    if (settings.dla_local_dram_size != 1073741824){
+    if (settings.dla_local_dram_size != 1073741824) {
       cfg->setMemoryPoolLimit(nvinfer1::MemoryPoolType::kDLA_LOCAL_DRAM, settings.dla_local_dram_size);
     }
-    if (settings.dla_global_dram_size != 536870912){
+    if (settings.dla_global_dram_size != 536870912) {
       cfg->setMemoryPoolLimit(nvinfer1::MemoryPoolType::kDLA_GLOBAL_DRAM, settings.dla_global_dram_size);
     }
   }

core/conversion/converters/converter_util.cpp

@@ -207,13 +207,13 @@ nvinfer1::ITensor* clamp(
     nvinfer1::ITensor* lower_bound,
     nvinfer1::ITensor* upper_bound,
     std::string const& name) {
-
   auto max_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kMAX, x, lower_bound, "max layer for " + name);
   TORCHTRT_CHECK(max_layer, "Unable to create max layer for clamp");
   LOG_DEBUG(ctx->logger, "Create " << max_layer->getName() << " for clamp");
   auto max_itensor = max_layer->getOutput(0);
 
-  auto min_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kMIN, max_itensor, upper_bound, "min layer for " + name);
+  auto min_layer =
+      add_elementwise(ctx, nvinfer1::ElementWiseOperation::kMIN, max_itensor, upper_bound, "min layer for " + name);
   TORCHTRT_CHECK(min_layer, "Unable to create min layer for clamp");
   LOG_DEBUG(ctx->logger, "Create " << min_layer->getName() << " for clamp");
   auto min_itensor = min_layer->getOutput(0);
@@ -227,13 +227,13 @@ nvinfer1::ITensor* clamp_to_input_dim(
     nvinfer1::ITensor* input_dim,
     int nbdims,
     std::string const& name) {
-
   auto zero = torch::zeros({nbdims}).to(torch::kI32);
   auto zero_itensor = tensor_to_const(ctx, zero);
   auto one = torch::ones({nbdims}).to(torch::kI32);
   auto one_itensor = tensor_to_const(ctx, one);
 
-  auto upper_bound_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kSUB, input_dim, one_itensor, "sub layer for " + name);
+  auto upper_bound_layer =
+      add_elementwise(ctx, nvinfer1::ElementWiseOperation::kSUB, input_dim, one_itensor, "sub layer for " + name);
   TORCHTRT_CHECK(upper_bound_layer, "Unable to create sub layer for clamp to inputDim");
   LOG_DEBUG(ctx->logger, "Create " << upper_bound_layer->getName() << " for clamp to inputDim");
   auto upper_bound = upper_bound_layer->getOutput(0);
@@ -243,7 +243,8 @@ nvinfer1::ITensor* clamp_to_input_dim(
   LOG_DEBUG(ctx->logger, "Create " << max_layer->getName() << " for clamp to inputDim");
   auto max_itensor = max_layer->getOutput(0);
 
-  auto min_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kMIN, max_itensor, upper_bound, "min layer for " + name);
+  auto min_layer =
+      add_elementwise(ctx, nvinfer1::ElementWiseOperation::kMIN, max_itensor, upper_bound, "min layer for " + name);
   TORCHTRT_CHECK(min_layer, "Unable to create min_layer for clamp to inputDim");
   LOG_DEBUG(ctx->logger, "Create " << min_layer->getName() << " for clamp to inputDim");
   auto min_itensor = min_layer->getOutput(0);
@@ -257,7 +258,6 @@ nvinfer1::ITensor* normalize_indices(
     nvinfer1::ITensor* indices,
     int nbdims,
     std::string const& name) {
-
   auto zero = torch::zeros({nbdims}).to(torch::kI32);
   auto neg = -torch::ones({nbdims}).to(torch::kI32);
   auto zero_itensor = tensor_to_const(ctx, zero);
@@ -307,17 +307,20 @@ nvinfer1::ITensor* get_slice_size(
   at::Tensor one_tensor = torch::ones({nbdims}).to(torch::kI32);
   auto one_itensor = tensor_to_const(ctx, one_tensor);
 
-  auto sub_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kSUB, end, start, "get_slice_size sub layer for " + name);
+  auto sub_layer =
+      add_elementwise(ctx, nvinfer1::ElementWiseOperation::kSUB, end, start, "get_slice_size sub layer for " + name);
   TORCHTRT_CHECK(sub_layer, "Unable to create sub layer in calculate_output_size");
   LOG_DEBUG(ctx->logger, "Create " << sub_layer->getName() << " for calculate_output_size");
   auto sub_itensor = sub_layer->getOutput(0);
 
-  auto div_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kDIV, sub_itensor, stride, "get_slice_size div layer for " + name);
+  auto div_layer = add_elementwise(
+      ctx, nvinfer1::ElementWiseOperation::kDIV, sub_itensor, stride, "get_slice_size div layer for " + name);
   TORCHTRT_CHECK(div_layer, "Unable to create div layer in calculate_output_size");
   LOG_DEBUG(ctx->logger, "Create " << div_layer->getName() << " for calculate_output_size");
   auto div_itensor = div_layer->getOutput(0);
 
-  auto add_layer = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kSUM, div_itensor, one_itensor, "get_slice_size sum layer for " + name);
+  auto add_layer = add_elementwise(
+      ctx, nvinfer1::ElementWiseOperation::kSUM, div_itensor, one_itensor, "get_slice_size sum layer for " + name);
   TORCHTRT_CHECK(add_layer, "Unable to create add layer in calculate_output_size");
   LOG_DEBUG(ctx->logger, "Create " << add_layer->getName() << " for calculate_output_size");
   auto size_itensor = add_layer->getOutput(0);

core/conversion/converters/converter_util.h

@@ -1,8 +1,8 @@
 #pragma once
 
+#include <limits>
 #include <map>
 #include <string>
-#include <limits>
 
 #include "core/conversion/conversionctx/ConversionCtx.h"
 #include "core/conversion/converters/Weights.h"