arm_compute v18.05HEADmaster

1 files changed, 61 insertions, 4 deletions

diff --git a/tests/AssetsLibrary.h b/tests/AssetsLibrary.h
index 7e2a042e9..1fba3d4b4 100644
--- a/tests/AssetsLibrary.h
+++ b/tests/AssetsLibrary.h
@@ -66,27 +66,39 @@ public:
      */
     AssetsLibrary(std::string path, std::random_device::result_type seed);
 
-    /** Path to assets directory used to initialise library. */
+    /** Path to assets directory used to initialise library.
+     *
+     * @return the path to the assets directory.
+     */
     std::string path() const;
 
-    /** Seed that is used to fill tensors with random values. */
+    /** Seed that is used to fill tensors with random values.
+     *
+     * @return the initial random seed.
+     */
     std::random_device::result_type seed() const;
 
     /** Provides a tensor shape for the specified image.
      *
      * @param[in] name Image file used to look up the raw tensor.
+     *
+     * @return the tensor shape for the specified image.
      */
     TensorShape get_image_shape(const std::string &name);
 
-    /** Provides a contant raw tensor for the specified image.
+    /** Provides a constant raw tensor for the specified image.
      *
      * @param[in] name Image file used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image.
      */
     const RawTensor &get(const std::string &name) const;
 
     /** Provides a raw tensor for the specified image.
      *
      * @param[in] name Image file used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image.
      */
     RawTensor get(const std::string &name);
 
@@ -96,6 +108,8 @@ public:
      * @param[in] name         Image file used to initialise the tensor.
      * @param[in] data_type    Data type used to initialise the tensor.
      * @param[in] num_channels Number of channels used to initialise the tensor.
+     *
+     * @return a raw tensor for the specified image.
      */
     RawTensor get(const std::string &name, DataType data_type, int num_channels = 1) const;
 
@@ -104,6 +118,8 @@ public:
      *
      * @param[in] name   Image file used to look up the raw tensor.
      * @param[in] format Format used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image.
      */
     const RawTensor &get(const std::string &name, Format format) const;
 
@@ -112,6 +128,8 @@ public:
      *
      * @param[in] name   Image file used to look up the raw tensor.
      * @param[in] format Format used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image.
      */
     RawTensor get(const std::string &name, Format format);
 
@@ -123,6 +141,8 @@ public:
      *
      * @note The channel has to be unambiguous so that the format can be
      *       inferred automatically.
+     *
+     * @return a raw tensor for the specified image channel.
      */
     const RawTensor &get(const std::string &name, Channel channel) const;
 
@@ -134,6 +154,8 @@ public:
      *
      * @note The channel has to be unambiguous so that the format can be
      *       inferred automatically.
+     *
+     * @return a raw tensor for the specified image channel.
      */
     RawTensor get(const std::string &name, Channel channel);
 
@@ -143,6 +165,8 @@ public:
      * @param[in] name    Image file used to look up the raw tensor.
      * @param[in] format  Format used to look up the raw tensor.
      * @param[in] channel Channel used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image channel.
      */
     const RawTensor &get(const std::string &name, Format format, Channel channel) const;
 
@@ -152,6 +176,8 @@ public:
      * @param[in] name    Image file used to look up the raw tensor.
      * @param[in] format  Format used to look up the raw tensor.
      * @param[in] channel Channel used to look up the raw tensor.
+     *
+     * @return a raw tensor for the specified image channel.
      */
     RawTensor get(const std::string &name, Format format, Channel channel);
 
@@ -326,6 +352,16 @@ public:
     template <typename T>
     void fill_layer_data(T &&tensor, std::string name) const;
 
+    /** Fill a tensor with a constant value
+     *
+     * @param[in, out] tensor To be filled tensor.
+     * @param[in]      value  Value to be assigned to all elements of the input tensor.
+     *
+     * @note    @p value must be of the same type as the data type of @p tensor
+     */
+    template <typename T, typename D>
+    void fill_tensor_value(T &&tensor, D value) const;
+
 private:
     // Function prototype to convert between image formats.
     using Converter = void (*)(const RawTensor &src, RawTensor &dst);
@@ -420,10 +456,25 @@ void AssetsLibrary::fill(T &&tensor, D &&distribution, std::random_device::resul
 
     std::mt19937 gen(_seed + seed_offset);
 
+    const bool  is_nhwc = tensor.data_layout() == DataLayout::NHWC;
+    TensorShape shape(tensor.shape());
+
+    if(is_nhwc)
+    {
+        // Ensure that the equivalent tensors will be filled for both data layouts
+        permute(shape, PermutationVector(1U, 2U, 0U));
+    }
+
     // Iterate over all elements
     for(int element_idx = 0; element_idx < tensor.num_elements(); ++element_idx)
     {
-        const Coordinates id = index2coord(tensor.shape(), element_idx);
+        Coordinates id = index2coord(shape, element_idx);
+
+        if(is_nhwc)
+        {
+            // Write in the correct id for permuted shapes
+            permute(id, PermutationVector(2U, 0U, 1U));
+        }
 
         // Iterate over all channels
         for(int channel = 0; channel < tensor.num_channels(); ++channel)
@@ -748,6 +799,12 @@ void AssetsLibrary::fill_layer_data(T &&tensor, std::string name) const
         });
     }
 }
+
+template <typename T, typename D>
+void AssetsLibrary::fill_tensor_value(T &&tensor, D value) const
+{
+    fill_tensor_uniform(tensor, 0, value, value);
+}
 } // namespace test
 } // namespace arm_compute
 #endif /* __ARM_COMPUTE_TEST_TENSOR_LIBRARY_H__ */