From 4b201bc922bc89522c15ba171e82bd77e54b7b62 Mon Sep 17 00:00:00 2001 From: Shwetank Singh <ssingh@tenstorrent.com> Date: Mon, 23 Dec 2024 08:55:56 +0000 Subject: [PATCH] #0: clean up --- .../tt/ttnn_functional_resnet50_new_conv_api.py | 3 --- .../functional_unet/tt/unet_shallow_ttnn.py | 1 - .../conv/conv2d/prepare_conv2d_weights.cpp | 12 ++++++------ 3 files changed, 6 insertions(+), 10 deletions(-) diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py index 7a2f400d4377..2751a5cfabb2 100644 --- a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py +++ b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py @@ -258,7 +258,6 @@ def __call__( } if not ttnn.is_tensor_storage_on_device(self.conv1_weight_tensor): - print("preparing conv1 weights") self.conv1_weight_tensor = ttnn.prepare_conv_weights( weight_tensor=self.conv1_weight_tensor, weights_format="OIHW", @@ -384,7 +383,6 @@ def __call__( } if not ttnn.is_tensor_storage_on_device(self.conv2_weight_tensor): - print("Preparing conv2 weights") self.conv2_weight_tensor = ttnn.prepare_conv_weights( weight_tensor=self.conv2_weight_tensor, weights_format="OIHW", @@ -465,7 +463,6 @@ def __call__( } if not ttnn.is_tensor_storage_on_device(self.conv3_weight_tensor): - print("Preparing conv3 weights") self.conv3_weight_tensor = ttnn.prepare_conv_weights( weight_tensor=self.conv3_weight_tensor, weights_format="OIHW", diff --git a/models/experimental/functional_unet/tt/unet_shallow_ttnn.py b/models/experimental/functional_unet/tt/unet_shallow_ttnn.py index bf6903dd75b7..ed34523c15ec 100644 --- a/models/experimental/functional_unet/tt/unet_shallow_ttnn.py +++ b/models/experimental/functional_unet/tt/unet_shallow_ttnn.py @@ -147,7 +147,6 @@ def __init__( self.bias = ttnn.from_torch(bias, dtype=ttnn.float32, mesh_mapper=mesh_mapper) def __call__(self, x): - print(ttnn.get_memory_config(x)) conv_kwargs = { "input_layout": x.get_layout(), "in_channels": self.in_channels, diff --git a/ttnn/cpp/ttnn/operations/conv/conv2d/prepare_conv2d_weights.cpp b/ttnn/cpp/ttnn/operations/conv/conv2d/prepare_conv2d_weights.cpp index 07eeb19b254c..9aba17b48ce0 100644 --- a/ttnn/cpp/ttnn/operations/conv/conv2d/prepare_conv2d_weights.cpp +++ b/ttnn/cpp/ttnn/operations/conv/conv2d/prepare_conv2d_weights.cpp @@ -188,8 +188,8 @@ std::pair<ttnn::Tensor, std::optional<ttnn::Tensor>> prepare_conv_weights_biases const bool parameters_on_device, bool is_non_tile_mul_width) { - std::cout << "pcwbmtd " << input_channels_alignment << " " << weight_block_h_ntiles << " " << weight_block_w_ntiles << " " << groups << " " << act_block_h_ntiles << " " << input_width << " " << is_non_tile_mul_width << std::endl; - std::cout << "parallel config" << (int)parallel_config.shard_scheme << " " << (int)parallel_config.shard_orientation << std::endl; + // std::cout << "pcwbmtd " << input_channels_alignment << " " << weight_block_h_ntiles << " " << weight_block_w_ntiles << " " << groups << " " << act_block_h_ntiles << " " << input_width << " " << is_non_tile_mul_width << std::endl; + // std::cout << "parallel config" << (int)parallel_config.shard_scheme << " " << (int)parallel_config.shard_orientation << std::endl; validate_weight_tensor(weight_tensor); ttnn::Tensor weight_tensor_; // tensor to return @@ -226,7 +226,7 @@ std::pair<ttnn::Tensor, std::optional<ttnn::Tensor>> prepare_conv_weights_biases uint32_t window_h = weights_shape[2]; uint32_t window_w = weights_shape[3]; - std::cout << "for bias -> " << out_channels << std::endl; + // std::cout << "for bias -> " << out_channels << std::endl; uint32_t num_cores_channels = get_num_cores_channels_from_parallel_config(parallel_config); uint32_t out_channels_padded = tt::round_up(out_channels, num_cores_channels * tt::constants::TILE_WIDTH); @@ -313,8 +313,8 @@ ttnn::Tensor prepare_conv_weights( T *device, const std::optional<const Conv2dConfig>& conv_config_, const std::optional<const DeviceComputeKernelConfig>& compute_config_) { - std::cout << "prepare conv weight" << std::endl; - std::cout << "input_memory_config -> " << input_memory_config << std::endl; + // std::cout << "prepare conv weight" << std::endl; + // std::cout << "input_memory_config -> " << input_memory_config << std::endl; TT_FATAL(!ttnn::is_tensor_on_device_or_multidevice(weight_tensor), "Error: weight tensor must be on host for preparation."); Conv2dConfig conv_config = conv_config_.value_or(Conv2dConfig()); DeviceComputeKernelConfig compute_config = compute_config_.value_or(init_device_compute_kernel_config( @@ -407,7 +407,7 @@ ttnn::Tensor prepare_conv_bias( TT_FATAL(!ttnn::is_tensor_on_device_or_multidevice(bias_tensor), "Error: bias tensor must be on host for preparation."); - std::cout << "prepare conv bias" << std::endl; + // std::cout << "prepare conv bias" << std::endl; const bool mm_conv = use_matmul_for_1x1_conv(kernel_size, stride, padding, dilation, groups); const uint32_t output_height = ((input_height - kernel_size[0] - ((kernel_size[0] - 1 ) * (dilation[0] - 1)) + 2 * padding[0]) / stride[0]) + 1;