Add URL to Keras CNN MNIST model; make URL constants more concise

Author: milancurcic

example/mnist_from_keras.f90

@@ -4,19 +4,19 @@ program mnist_from_keras
   ! from an HDF5 file and running an inferrence on the testing dataset.
 
   use nf, only: network, label_digits, load_mnist
-  use nf_datasets, only: download_and_unpack, keras_model_dense_mnist_url
+  use nf_datasets, only: download_and_unpack, keras_dense_mnist_url
 
   implicit none
 
   type(network) :: net
   real, allocatable :: training_images(:,:), training_labels(:)
   real, allocatable :: validation_images(:,:), validation_labels(:)
   real, allocatable :: testing_images(:,:), testing_labels(:)
-  character(*), parameter :: test_data_path = 'keras_dense_mnist.h5'
+  character(*), parameter :: keras_dense_path = 'keras_dense_mnist.h5'
   logical :: file_exists
 
-  inquire(file=test_data_path, exist=file_exists)
-  if (.not. file_exists) call download_and_unpack(keras_model_dense_mnist_url)
+  inquire(file=keras_dense_path, exist=file_exists)
+  if (.not. file_exists) call download_and_unpack(keras_dense_mnist_url)
 
   call load_mnist(training_images, training_labels, &
                   validation_images, validation_labels, &
@@ -25,7 +25,7 @@ program mnist_from_keras
   print '("Loading a pre-trained MNIST model from Keras")'
   print '(60("="))'
 
-  net = network(test_data_path)
+  net = network(keras_dense_path)
 
   call net % print_info()
 

src/nf/nf_datasets.f90

@@ -8,13 +8,19 @@ module nf_datasets
 
   private
 
-  public :: download_and_unpack, keras_model_dense_mnist_url, mnist_url
+  public :: &
+    download_and_unpack, &
+    keras_cnn_mnist_url, &
+    keras_dense_mnist_url, &
+    mnist_url
 
   character(*), parameter :: keras_snippets_baseurl = &
     'https://github.com/neural-fortran/keras-snippets/files'
   character(*), parameter :: neural_fortran_baseurl = &
     'https://github.com/modern-fortran/neural-fortran/files'
-  character(*), parameter :: keras_model_dense_mnist_url = &
+  character(*), parameter :: keras_cnn_mnist_url = &
+    keras_snippets_baseurl // '/8892585/keras_cnn_mnist.tar.gz'
+  character(*), parameter :: keras_dense_mnist_url = &
     keras_snippets_baseurl // '/8788739/keras_dense_mnist.tar.gz'
   character(*), parameter :: mnist_url = &
     neural_fortran_baseurl // '/8498876/mnist.tar.gz'

test/test_dense_network_from_keras.f90

@@ -2,7 +2,7 @@ program test_dense_network_from_keras
 
   use iso_fortran_env, only: stderr => error_unit
   use nf, only: network
-  use nf_datasets, only: download_and_unpack, keras_model_dense_mnist_url
+  use nf_datasets, only: download_and_unpack, keras_dense_mnist_url
 
   implicit none
 
@@ -12,7 +12,7 @@ program test_dense_network_from_keras
   logical :: ok = .true.
 
   inquire(file=test_data_path, exist=file_exists)
-  if (.not. file_exists) call download_and_unpack(keras_model_dense_mnist_url)
+  if (.not. file_exists) call download_and_unpack(keras_dense_mnist_url)
 
   net = network(test_data_path)
 

test/test_io_hdf5.f90

@@ -1,7 +1,7 @@
 program test_io_hdf5
 
   use iso_fortran_env, only: stderr => error_unit
-  use nf_datasets, only: download_and_unpack, keras_model_dense_mnist_url
+  use nf_datasets, only: download_and_unpack, keras_dense_mnist_url
   use nf_io_hdf5, only: hdf5_attribute_string, get_hdf5_dataset
 
   implicit none
@@ -14,7 +14,7 @@ program test_io_hdf5
   logical :: ok = .true.
 
   inquire(file=test_data_path, exist=file_exists)
-  if (.not. file_exists) call download_and_unpack(keras_model_dense_mnist_url)
+  if (.not. file_exists) call download_and_unpack(keras_dense_mnist_url)
 
   attr = hdf5_attribute_string(test_data_path, '.', 'backend')
 

test/test_keras_read_model.f90

@@ -1,14 +1,16 @@
 program test_keras_read_model
 
   use iso_fortran_env, only: stderr => error_unit
-  use nf_datasets, only: download_and_unpack, keras_model_dense_mnist_url
+  use nf_datasets, only: download_and_unpack, keras_dense_mnist_url, &
+    keras_cnn_mnist_url
   use nf_keras, only: get_keras_h5_layers, keras_layer
   use nf, only: layer, network, dense, input
 
   implicit none
 
   character(:), allocatable :: model_config_string
-  character(*), parameter :: test_data_path = 'keras_dense_mnist.h5'
+  character(*), parameter :: keras_dense_path = 'keras_dense_mnist.h5'
+  character(*), parameter :: keras_cnn_path = 'keras_cnn_mnist.h5'
 
   type(keras_layer), allocatable :: keras_layers(:)
 
@@ -19,10 +21,12 @@ program test_keras_read_model
   logical :: file_exists
   logical :: ok = .true.
 
-  inquire(file=test_data_path, exist=file_exists)
-  if (.not. file_exists) call download_and_unpack(keras_model_dense_mnist_url)
+  ! First test the dense model
 
-  keras_layers = get_keras_h5_layers(test_data_path)
+  inquire(file=keras_dense_path, exist=file_exists)
+  if (.not. file_exists) call download_and_unpack(keras_dense_mnist_url)
+
+  keras_layers = get_keras_h5_layers(keras_dense_path)
 
   if (size(keras_layers) /= 3) then
     ok = .false.
@@ -51,6 +55,13 @@ program test_keras_read_model
       'Keras second and third layers should be dense.. failed'
   end if
 
+  ! Now testing for the CNN model
+
+  inquire(file=keras_cnn_path, exist=file_exists)
+  if (.not. file_exists) call download_and_unpack(keras_cnn_mnist_url)
+
+  keras_layers = get_keras_h5_layers(keras_cnn_path)
+
   if (ok) then
     print '(a)', 'test_keras_read_model: All tests passed.'
   else