chore(examples): match program names to file names

example/concurrent-inferences.f90

@@ -1,6 +1,6 @@
 ! Copyright (c), The Regents of the University of California
 ! Terms of use are as specified in LICENSE.txt
-program concurrent_inference
+program concurrent_inferences
   !! This program demonstrates how to read a neural network from a JSON file
   !! and use the network to perform concurrent inferences.
   use inference_engine_m, only : inference_engine_t, tensor_t
@@ -16,12 +16,12 @@ program concurrent_inference
 
   if (len(network_file_name%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run --example identity -- --network "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run --example concurrent-inferences -- --network "<file-name>"' 
   end if
 
   block 
     type(inference_engine_t) network, inference_engine
-    type(tensor_t), allocatable :: inputs(:,:,:), outputs(:,:,:) 
+    type(tensor_t), allocatable :: inputs(:,:,:), outputs(:,:,:)
     real, allocatable :: input_components(:,:,:,:)
     integer, parameter :: lat=263, lon=317, lev=15 ! latitudes, longitudes, levels (elevations)
     integer i, j, k

example/learn-addition.f90

@@ -1,6 +1,6 @@
 ! Copyright (c), The Regents of the University of California
 ! Terms of use are as specified in LICENSE.txt
-module add_inputs
+module addition_m
   !! Define a function that produces the desired network output for a given network input
   use inference_engine_m, only : tensor_t
   use assert_m, only : assert
@@ -18,13 +18,13 @@ elemental function y(x_tensor) result(a_tensor)
 
 end module
 
-program train_polynomials
+program learn_addition
   !! This trains a neural network to learn the following six polynomial functions of its eight inputs.
   use inference_engine_m, only : &
     inference_engine_t, trainable_engine_t, mini_batch_t, tensor_t, input_output_pair_t, shuffle, relu_t
   use sourcery_m, only : string_t, file_t, command_line_t, bin_t, csv
   use assert_m, only : assert, intrinsic_array_t
-  use add_inputs, only : y
+  use addition_m, only : y
   implicit none
 
   type(string_t) intial_network_file, final_network_file
@@ -34,7 +34,7 @@ program train_polynomials
 
   if (len(final_network_file%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run --example train-polynomials -- --output-file "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run --example learn-addition -- --output-file "<file-name>"' 
   end if
 
   block

example/learn-exponentiation.f90

@@ -1,6 +1,6 @@
 ! Copyright (c), The Regents of the University of California
 ! Terms of use are as specified in LICENSE.txt
-module raise_inputs_to_a_power
+module exponentiation_m
   !! Define a function that produces the desired network output for a given network input
   use inference_engine_m, only : tensor_t
   use assert_m, only : assert
@@ -18,13 +18,13 @@ elemental function y(x_tensor) result(a_tensor)
 
 end module
 
-program train_polynomials
+program learn_exponentiation
   !! This trains a neural network to learn the following six polynomial functions of its eight inputs.
   use inference_engine_m, only : &
     inference_engine_t, trainable_engine_t, mini_batch_t, tensor_t, input_output_pair_t, shuffle, relu_t
   use sourcery_m, only : string_t, file_t, command_line_t, bin_t, csv
   use assert_m, only : assert, intrinsic_array_t
-  use raise_inputs_to_a_power, only : y
+  use exponentiation_m, only : y
   implicit none
 
   type(string_t) intial_network_file, final_network_file

example/learn-microphysics-procedures.f90

@@ -19,7 +19,7 @@ program learn_microphysics_procedures
 
   if (len(network_file%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run learn_microphysics_procedures -- --output-file "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run learn-microphysics-procedures -- --output-file "<file-name>"' 
   end if
 
   call system_clock(counter_start, clock_rate)

example/learn-multiplication.f90

@@ -18,7 +18,7 @@ elemental function y(x_tensor) result(a_tensor)
 
 end module
 
-program train_polynomials
+program learn_multiplication
   !! This trains a neural network to learn the following six polynomial functions of its eight inputs.
   use inference_engine_m, only : &
     inference_engine_t, trainable_engine_t, mini_batch_t, tensor_t, input_output_pair_t, shuffle, relu_t
@@ -34,7 +34,7 @@ program train_polynomials
 
   if (len(final_network_file%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run --example train-polynomials -- --output-file "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run --example learn-multiplication -- --output-file "<file-name>"' 
   end if
 
   block

example/learn-power-series.f90

@@ -18,7 +18,7 @@ elemental function y(x_in) result(a)
 
 end module
 
-program train_polynomials
+program learn_power_series
   !! This trains a neural network to learn the following six polynomial functions of its eight inputs.
   use inference_engine_m, only : &
     inference_engine_t, trainable_engine_t, mini_batch_t, tensor_t, input_output_pair_t, shuffle, relu_t
@@ -34,7 +34,7 @@ program train_polynomials
 
   if (len(final_network_file%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run --example train-polynomials -- --output-file "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run --example learn-power-series -- --output-file "<file-name>"' 
   end if
 
   block

example/write-read-infer.f90

@@ -19,7 +19,7 @@ program write_read_infer
 
   if (len(file_name%string())==0) then
     error stop new_line('a') // new_line('a') // &
-      'Usage: ./build/run-fpm.sh run --example identity -- --output-file "<file-name>"' 
+      'Usage: ./build/run-fpm.sh run --example write-read-infer -- --output-file "<file-name>"' 
   end if
 
   call write_read_query_infer(file_name)