Remove unused code in arm_conv/depthwise/

* Removed header files in arm_conv/depthwise

* Resolves MLCE-990

Change-Id: Iacddd80e2d83ff0fbafb817014f90c5bc80dab3c
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8946
Reviewed-by: Andrew Mundy <Andrew.mundy@arm.com>
Reviewed-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 0 insertions, 251 deletions

diff --git a/src/core/NEON/kernels/arm_conv/depthwise/depthwise_depthfirst_multiplier_quantized.hpp b/src/core/NEON/kernels/arm_conv/depthwise/depthwise_depthfirst_multiplier_quantized.hpp
deleted file mode 100644
index 07ce0d3b55..0000000000
--- a/src/core/NEON/kernels/arm_conv/depthwise/depthwise_depthfirst_multiplier_quantized.hpp
+++ /dev/null
@@ -1,251 +0,0 @@
-/*
- * Copyright (c) 2021 Arm Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-
-#pragma once
-
-#include "depthwise_depthfirst_multiplier.hpp"
-
-namespace arm_conv {
-namespace depthwise {
-
-template <class strategy>
-class DepthwiseDepthfirstWithMultiplierQuantized :
-  public DepthwiseCommon<typename strategy::input_type,
-                         typename strategy::weight_type,
-                         typename strategy::return_type>
-{
-  using Parent = DepthwiseCommon<typename strategy::input_type,
-                                 typename strategy::weight_type,
-                                 typename strategy::return_type>;
-  using TInput = typename strategy::input_type;
-  using TWeight = typename strategy::weight_type;
-  using TOutput = typename strategy::return_type;
-
-  const arm_gemm::Requantize32 m_qp;
-
-  size_t sizeof_output_buffer(unsigned int n_channels) const
-  {
-    const unsigned int vl = arm_gemm::utils::get_vector_length<typename strategy::return_type>(strategy::vl_type);
-    const auto rounded_channels = arm_gemm::roundup(n_channels, vl);
-    return sizeof(typename strategy::return_type) * rounded_channels;
-  }
-
-  public:
-  DepthwiseDepthfirstWithMultiplierQuantized(const DepthwiseArgs &args, const arm_gemm::Requantize32 &qp)
-    : Parent(args), m_qp(qp)
-  {
-  }
-
-  DepthwiseDepthfirstWithMultiplierQuantized(DepthwiseDepthfirstWithMultiplierQuantized &) = delete;
-  DepthwiseDepthfirstWithMultiplierQuantized &operator=(DepthwiseDepthfirstWithMultiplierQuantized &) = delete;
-
-  size_t get_storage_size(void) const override
-  {
-    // We produce VL<int32_t> channels at a time, for each of these blocks of
-    // channels we store a vector of biases, weights (complicated) and
-    // requantize parameters.
-    const unsigned int iter_length =
-      arm_gemm::utils::get_vector_length<int32_t>(strategy::vl_type);
-    const unsigned int n_iters =
-      this->m_args.input_channels * arm_gemm::iceildiv(this->m_args.channel_multiplier, iter_length);
-
-    // Compute the cost of storing the weights
-    const unsigned int n_dots_per_kernel_row = arm_gemm::iceildiv(strategy::kernel_cols, 4u);
-
-    return n_iters * iter_length * (
-        sizeof(int32_t) +  // Bias
-        4 * n_dots_per_kernel_row * strategy::kernel_rows * sizeof(TWeight) +  // Weights
-        2 * sizeof(int32_t)  // Requantisation parameters
-    );
-  }
-
-  // We'll want an optimised version of this, but for now a C++ implementation
-  // is probably sufficient.
-  void pack_parameters(void *_buffer, const void *_biases, const void *_weights, size_t ld_weight_col, size_t ld_weight_row) override
-  {
-    auto buffer = static_cast<uint8_t *>(_buffer);
-    auto biases = static_cast<const int32_t *>(_biases);
-    auto weights = static_cast<const TWeight *>(_weights);
-    auto requant_muls = m_qp.per_channel_muls;
-    auto requant_shifts = m_qp.per_channel_right_shifts;
-
-    const unsigned int iter_length =
-      arm_gemm::utils::get_vector_length<int32_t>(strategy::vl_type);
-    const unsigned int n_iters_per_input_channel =
-      arm_gemm::iceildiv(this->m_args.channel_multiplier, iter_length);
-
-    const unsigned int n_dots_per_kernel_row = arm_gemm::iceildiv(strategy::kernel_cols, 4u);
-
-    const size_t iter_stride = iter_length * (
-        sizeof(int32_t) +  // Bias
-        4 * n_dots_per_kernel_row * strategy::kernel_rows * sizeof(int8_t) +  // Weights
-        2 * sizeof(int32_t)  // Requantisation parameters
-    );
-
-    ld_weight_col = (ld_weight_col == 0) ? this->m_args.input_channels * this->m_args.channel_multiplier : ld_weight_col;
-    ld_weight_row = (ld_weight_row == 0) ? this->m_args.kernel_cols * ld_weight_col : ld_weight_row;
-
-    for (unsigned int input_channel = 0; input_channel < this->m_args.input_channels; input_channel++)
-    {
-      auto buffer_input_channel = buffer + input_channel * n_iters_per_input_channel * iter_stride;
-      auto weights_input_channel = weights + input_channel * this->m_args.channel_multiplier;
-
-      for (unsigned int iter = 0; iter < n_iters_per_input_channel; iter++)
-      {
-        // Get a pointer to the start of this portion of the buffer; consequently
-        // derive pointers to the bias, weight and requantisation portions of
-        // this frame.
-        auto buffer_base = buffer_input_channel + iter_stride * iter;
-        auto buffer_biases = reinterpret_cast<int32_t *>(buffer_base);
-        auto buffer_weights = buffer_base + sizeof(int32_t) * iter_length;
-        auto buffer_requant_mul = reinterpret_cast<int32_t *>(
-          buffer_weights + strategy::kernel_rows * n_dots_per_kernel_row * 4 * iter_length);
-        auto buffer_requant_shift = buffer_requant_mul + iter_length;
-        auto weights_base = weights_input_channel + iter * iter_length;
-
-        // Hence work through the data for this iteration, on a
-        // channel-by-channel basis.
-        const auto this_iter_length = std::min<unsigned int>(
-          iter_length, this->m_args.channel_multiplier - iter * iter_length
-        );
-        for (unsigned int i = 0; i < this_iter_length; i++)
-        {
-          auto weights_channel = weights_base + i;
-
-          // Read the bias value, we modify this as we read the weights.
-          auto bias_value = biases == nullptr ? 0 : *(biases++);
-          int32_t elements_sum = 0;
-
-          // Read through the kernel; for each row, marshal together as many dot
-          // product terms as are required.
-          for (unsigned int ki = 0; ki < strategy::kernel_rows; ki++)
-          {
-            auto buffer_row = buffer_weights + i*4 + ki * 4 * n_dots_per_kernel_row * iter_length;
-            auto weights_row = weights_channel + ki * ld_weight_row;
-
-            unsigned int kj = 0;
-            for (; kj < strategy::kernel_cols; kj++)
-            {
-              // Determine which element to which we're writing
-              const auto dot = kj / 4;
-              const auto elem = kj % 4;
-
-              // Copy the value; include in the sum
-              const auto val = weights_row[kj * ld_weight_col];
-              buffer_row[dot * 4 * iter_length + elem] = val;
-              elements_sum += val;
-            }
-            for (; kj < 4 * n_dots_per_kernel_row; kj++)
-            {
-              const auto dot = kj / 4;
-              const auto elem = kj % 4;
-              buffer_row[dot * 4 * iter_length + elem] = 0;
-            }
-
-            buffer_row += 4 * n_dots_per_kernel_row * iter_length;
-          }
-
-          // Write back the bias and offset values
-          *(buffer_biases++) =
-            bias_value - m_qp.a_offset * elements_sum +
-            strategy::kernel_rows * strategy::kernel_cols * m_qp.a_offset * m_qp.b_offset;
-
-          // Write out the requantisation parameters
-          *(buffer_requant_mul++) = m_qp.per_channel_requant ? *(requant_muls++) : m_qp.per_layer_mul;
-          *(buffer_requant_shift++) = m_qp.per_channel_requant ? *(requant_shifts++) : m_qp.per_layer_right_shift;
-        }
-      }
-    }
-  }
-
-  size_t get_working_size(const unsigned int n_threads, const unsigned int n_channels) const override
-  {
-    const unsigned int n_output_channels = n_channels * this->m_args.channel_multiplier;
-    return n_threads * sizeof_output_buffer(n_output_channels);
-  }
-
-  using Parent::execute;
-  void execute(
-    const unsigned int batches,
-    const unsigned int input_height,
-    const unsigned int input_width,
-    const unsigned int input_channels,
-    const PaddingValues &padding,
-    const void *const _input,
-    const size_t ld_input_col,
-    const size_t ld_input_row,
-    const size_t ld_input_batch,
-    const void *const parameters,
-    const unsigned int output_height,
-    const unsigned int output_width,
-    void *const _output,
-    const size_t ld_output_col,
-    const size_t ld_output_row,
-    const size_t ld_output_batch,
-    void *const _working_space,
-    const unsigned int thread_id,
-    const unsigned int n_threads
-  ) const override
-  {
-    strategy strat(this->m_args.cpu_info);
-#ifdef CYCLE_PROFILING
-    arm_gemm::profiler prof;
-#endif
-
-    auto executefn = [strat, this] (
-      const TInput *const *const inptrs,
-      TOutput *const *const outptr_array,
-      const void *const params
-    ) {
-      strat.kernel(inptrs, outptr_array, params, this->m_args.channel_multiplier, m_qp);
-    };
-
-    // Get working space for this thread
-    uint8_t *const working_space = static_cast<uint8_t *>(_working_space) + get_working_size(1, input_channels) * thread_id;
-
-    // Determine the stride across blocks of parameters
-    const unsigned int iter_length =
-      arm_gemm::utils::get_vector_length<int32_t>(strategy::vl_type);
-    const unsigned int n_iters_per_input_channel = arm_gemm::iceildiv(this->m_args.channel_multiplier, iter_length);
-    const unsigned int n_dots_per_kernel_row = arm_gemm::iceildiv(strategy::kernel_cols, 4u);
-    const size_t param_stride = n_iters_per_input_channel * iter_length * (
-        sizeof(int32_t) +  // Bias
-        4 * n_dots_per_kernel_row * strategy::kernel_rows * sizeof(int8_t) +  // Weights
-        2 * sizeof(int32_t)  // Requantisation parameters
-    );
-
-    common::depthwise_multiplier_execute<strategy>(
-      executefn, m_qp.a_offset, this->m_args,
-      batches, input_height, input_width, input_channels, padding,
-      _input, ld_input_col, ld_input_row, ld_input_batch,
-      parameters, param_stride,
-      output_height, output_width,
-      _output, ld_output_col, ld_output_row, ld_output_batch,
-      working_space, thread_id, n_threads
-    );
-  }
-};
-
-}  // namespace depthwise
-}  // namespace arm_conv