nedtaylor · nedtaylor · Jun 28, 2024 · May 25, 2024 · Mar 20, 2024 · Mar 20, 2024
diff --git a/CHANGELOG b/CHANGELOG
@@ -15,6 +15,43 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Removed
 
+## [1.3.2] - 2024-06-28
+
+### Added
+- Added conv1d_layer_type
+- Added avgpool1d_layer_type
+- Added maxpool1d_layer_type
+- Added input2d_layer_type
+- Added statement of need to README
+
+### Changed
+
+### Fixed
+- Fix reference to fpm install in README
+- Fixed unallocated lr_decay reference
+- Fixed ifort and ifx compiler reference to temporary arrays
+- Fixed temporary array reference in tests
+- Fixed epsilon undefined value in mod_loss
+- Fixed project link in CMakeLists.txt
+
+### Removed
+
+## [1.3.1] - 2024-05-25
+
+### Added
+
+### Changed
+- Add reference to gcc 12.3 compatibility in README
+
+### Fixed
+- Fix attempt to assign size of random seed in random_setup
+- Fix attempt to assign size of random seed in test_network
+- Fix attempt to assing size of random seed in example/simple
+- Fix abstract interface use in base_layer_type
+- Add appropriate references to neural-fortran in CONTRIBUTING.md and associated procedures, and modules
+
+### Removed
+
 ## [1.3.0] - 2024-03-13
 
 ### Added

diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -15,7 +15,7 @@ project(athena NONE)
 set( LIB_NAME ${PROJECT_NAME} )
 set( PROJECT_DESCRIPTION
  "Fortran neural network" )
-set( PROJECT_URL "https://https://git.exeter.ac.uk/hepplestone/athena" )
+set( PROJECT_URL "https://github.com/nedtaylor/athena" )
 set( CMAKE_CONFIGURATION_TYPES "Release" "Parallel" "Serial" "Dev" "Debug" "Parallel_Dev"
  CACHE STRING "List of configurations types." )
 set( CMAKE_BUILD_TYPE "Release"
@@ -97,13 +97,16 @@ set(LIB_FILES
  mod_batchnorm1d_layer.f90
  mod_batchnorm2d_layer.f90
  mod_batchnorm3d_layer.f90
+ mod_conv1d_layer.f90
  mod_conv2d_layer.f90
  mod_conv3d_layer.f90
  mod_dropout_layer.f90
  mod_dropblock2d_layer.f90
  mod_dropblock3d_layer.f90
+ mod_avgpool1d_layer.f90
  mod_avgpool2d_layer.f90
  mod_avgpool3d_layer.f90
+ mod_maxpool1d_layer.f90
  mod_maxpool2d_layer.f90
  mod_maxpool3d_layer.f90
  mod_full_layer.f90
@@ -112,6 +115,7 @@ set(LIB_FILES
  mod_flatten3d_layer.f90
  mod_flatten4d_layer.f90
  mod_input1d_layer.f90
+ mod_input2d_layer.f90
  mod_input3d_layer.f90
  mod_input4d_layer.f90
  mod_container_layer.f90
@@ -221,6 +225,7 @@ if(BUILD_TESTS)
 endif()
 
 # add coverage compiler flags
-if (CMAKE_BUILD_TYPE MATCHES "Debug*" OR CMAKE_BUILD_TYPE MATCHES "Dev*")
+if ( ( CMAKE_Fortran_COMPILER MATCHES ".*gfortran.*" OR CMAKE_Fortran_COMPILER MATCHES ".*gcc.*" ) AND 
+ ( CMAKE_BUILD_TYPE MATCHES "Debug*" OR CMAKE_BUILD_TYPE MATCHES "Dev*" ) )
  append_coverage_compiler_flags()
 endif()
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -2,6 +2,8 @@
 
 This document outlines the organisation of the athena codebase to help guide code contributors.
 
+This document has been copied from the neural-fortran repository and used as a template from which to design this version. The original document can be found here: https://github.com/modern-fortran/neural-fortran/blob/main/CONTRIBUTING.md
+
 ## Overall code organization
 
 The source code organisation follows the usual `fpm` convention:

diff --git a/README.md b/README.md
@@ -25,6 +25,28 @@ It was decided that this project should be migrated to allow for better communit
 
 ---
 
+## Statement of need
+
+The ATHENA library leverages Fortran's strong support of array arithmatics, and its compatibility with parallel and high-performance computing resources.
+Additionally, there exist many improvements made available since Fortran 95, specifically in Fortran 2018 (Reid 2018) (and upcoming ones in Fortran 2023), as well as continued development by the Fortran Standards committee.
+All of this provides a clear incentive to develop further libraries and frameworks focused on providing machine learning capabilities to the Fortran community.
+
+While existing Fortran-based libraries, such as neural-fortran (Curcic 2019), address many aspects of neural networks,
+ATHENA provides implementation of some well-known features not currently available within other libraries; these features include batchnormalisation, regularisation layers (such as dropout and dropblock), and average pooling layers.
+Additionally, the library provides support for 1, 2, and 3D input data for most features currently implemented; this includes 1, 2, and 3D data for convolutional layers.
+Finally, the ATHENA library supports many convolutional techniques, including various data padding types, and stride.
+
+One of the primary intended applications of ATHENA is in materials science, which heavily utilises convolutional and graph neural networks for learning based on charge densities and atomic structures.
+Given the unique data structure of atomic configurations, specifically their graph-based nature, a specialised API must be developed to accommodate these needs.
+
+### References
+- Reid, J. (2018). The new features of fortran 2018. SIGPLAN Fortran Forum, 37(1), 5–43. https://doi.org/10.1145/3206214.3206215
+- Curcic, M. (2019). A parallel fortran framework for neural networks and deep learning. SIGPLAN Fortran Forum, 38(1), 4–21. https://doi.org/10.1145/3323057.3323059
+
+
+Documentation
+-----
+
 ATHENA is distributed with the following directories:
 
 | Directory | Description |
@@ -35,9 +57,6 @@ ATHENA is distributed with the following directories:
 | _test/_ | A set of test programs to check functionality of the library works after compilation |
 
 
-Documentation
------
-
 For extended details on the functionality of this library, please check out the [wiki](https://github.com/nedtaylor/athena/wiki)
 
 **NOTE: There currently exists no manual document. This will be included at a later date**
@@ -63,6 +82,10 @@ The library has been developed and tested using the following compilers:
 - ifort -- Intel 2021.10.0.20230609
 - ifx -- IntelLLVM 2023.2.0
 
+#### Tested compilers
+The library has also been tested with and found to support the following libraries:
+- gfortran -- gcc 12.3
+
 ### Building with fpm
 
 The library is set up to work with the Fortran Package Manager (fpm).
@@ -76,7 +99,7 @@ Run the following command in the repository main directory:
 
 To check whether ATHENA has installed correctly and that the compilation works as expected, the following command can be run:
 ```
- fpm test
+ fpm test --profile release
 ```
 
 This runs a set of test programs (found within the test/ directory) to ensure the expected output occurs when layers and networks are set up.
@@ -133,7 +156,7 @@ Using fpm, the examples are built alongside the library. To list all available e
 To run a particular example, execute the following command:
 
 ```
- fpm run --example [NAME]
+ fpm run --example [NAME] --profile release
 ```
 
 where [_NAME_] is the name of the example found in the list.

diff --git a/example/mnist/src/main.f90 b/example/mnist/src/main.f90
@@ -71,7 +71,7 @@ program mnist_example
 !!!-----------------------------------------------------------------------------
 !!! initialise random seed
 !!!-----------------------------------------------------------------------------
- call random_setup(seed, num_seed=1, restart=.false.)
+ call random_setup(seed, restart=.false.)
 
 
 !!!-----------------------------------------------------------------------------

diff --git a/example/mnist_3D/src/main.f90 b/example/mnist_3D/src/main.f90
@@ -72,7 +72,7 @@ program mnist_test
 !!!-----------------------------------------------------------------------------
 !!! initialise random seed
 !!!-----------------------------------------------------------------------------
- call random_setup(seed, num_seed=1, restart=.false.)
+ call random_setup(seed, restart=.false.)
 
 
 !!!-----------------------------------------------------------------------------

diff --git a/example/mnist_bn/src/main.f90 b/example/mnist_bn/src/main.f90
@@ -71,7 +71,7 @@ program mnist_example
 !!!-----------------------------------------------------------------------------
 !!! initialise random seed
 !!!-----------------------------------------------------------------------------
- call random_setup(seed, num_seed=1, restart=.false.)
+ call random_setup(seed, restart=.false.)
 
 
 !!!-----------------------------------------------------------------------------

diff --git a/example/mnist_drop/src/main.f90 b/example/mnist_drop/src/main.f90
@@ -71,7 +71,7 @@ program mnist_test
 !!!-----------------------------------------------------------------------------
 !!! initialise random seed
 !!!-----------------------------------------------------------------------------
- call random_setup(seed, num_seed=1, restart=.false.)
+ call random_setup(seed, restart=.false.)
 
 
 !!!-----------------------------------------------------------------------------

diff --git a/example/simple/src/main.f90 b/example/simple/src/main.f90
@@ -1,3 +1,6 @@
+!! This file contains a modified version of the "simple" example found in ...
+!! ... neural fortran:
+!! https://github.com/modern-fortran/neural-fortran/blob/main/example/simple.f90
 program simple
  use athena
  use constants_mnist, only: real12, pi
@@ -16,9 +19,8 @@ program simple
 
 
  !! set random seed
- seed_size = 8
  call random_seed(size=seed_size)
- seed = [1,1,1,1,1,1,1,1]
+ allocate(seed(seed_size), source = 1)
  call random_seed(put=seed)
 
  write(*,*) "Simple function approximation using a fully-connected neural network"

diff --git a/example/sine/src/main.f90 b/example/sine/src/main.f90
@@ -1,3 +1,6 @@
+!! This file contains a modified version of the "sine" example found in ...
+!! ... neural fortran:
+!! https://github.com/modern-fortran/neural-fortran/blob/main/example/sine.f90
 program sine
  use athena
  use constants_mnist, only: real12, pi

diff --git a/fpm.toml b/fpm.toml
@@ -1,5 +1,5 @@
 name = "athena"
-version = "1.3.0"
+version = "1.3.2"
 license = "MIT"
 author = "Ned Thaddeus Taylor"
 maintainer = "[email protected]"

diff --git a/src/athena.f90 b/src/athena.f90
@@ -49,6 +49,7 @@ module athena
 
  !! input layer types
  use input1d_layer, only: input1d_layer_type
+ use input2d_layer, only: input2d_layer_type
  use input3d_layer, only: input3d_layer_type
  use input4d_layer, only: input4d_layer_type
 
@@ -58,6 +59,7 @@ module athena
  use batchnorm3d_layer, only: batchnorm3d_layer_type, read_batchnorm3d_layer
 
  !! convolution layer types
+ use conv1d_layer, only: conv1d_layer_type, read_conv1d_layer
  use conv2d_layer, only: conv2d_layer_type, read_conv2d_layer
  use conv3d_layer, only: conv3d_layer_type, read_conv3d_layer
 
@@ -67,8 +69,10 @@ module athena
  use dropblock3d_layer, only: dropblock3d_layer_type, read_dropblock3d_layer
 
  !! pooling layer types
+ use avgpool1d_layer, only: avgpool1d_layer_type, read_avgpool1d_layer
  use avgpool2d_layer, only: avgpool2d_layer_type, read_avgpool2d_layer
  use avgpool3d_layer, only: avgpool3d_layer_type, read_avgpool3d_layer
+ use maxpool1d_layer, only: maxpool1d_layer_type, read_maxpool1d_layer
  use maxpool2d_layer, only: maxpool2d_layer_type, read_maxpool2d_layer
  use maxpool3d_layer, only: maxpool3d_layer_type, read_maxpool3d_layer