Reduce duplication in unit test names (#532)

* Shorten names for model unit tests
* Shorten names for tensor unit tests

Author: joewallwork

test/unit/model/unittest_model_constructors_destructors.pf

@@ -24,7 +24,7 @@ contains
   ! Unit test for the association of model pointers before and after loading
   ! a TorchScript model and after deletion.
   @test
-  subroutine test_torch_model_pointers()
+  subroutine test_pointers()
     type(torch_model) :: model
 
     ! Check the model pointer is not associated
@@ -38,6 +38,6 @@ contains
     call torch_model_delete(model)
     @assertFalse(c_associated(model%p))
 
-  end subroutine test_torch_model_pointers
+  end subroutine test_pointers
 
 end module unittest_model_constructors_destructors

test/unit/model/unittest_model_forward.pf

@@ -81,7 +81,7 @@ contains
 
   ! Unit test for checking values are propagated correctly through the test model
   @test(testparameters={get_parameters_short()})
-  subroutine test_torch_model_forward_value(this)
+  subroutine test_forward_value(this)
     use ftorch_tensor, only: torch_tensor_from_array
 
     implicit none
@@ -104,13 +104,13 @@ contains
     call torch_model_forward(model, input_tensors, output_tensors)
 
     expected = [0.0_wp, 2.0_wp, 4.0_wp, 6.0_wp, 8.0_wp]
-    @assertTrue(assert_allclose(output_array, expected, test_name="test_torch_model_forward_value"))
+    @assertTrue(assert_allclose(output_array, expected, test_name="test_forward_value"))
 
-  end subroutine test_torch_model_forward_value
+  end subroutine test_forward_value
 
   ! Unit test for checking that requires_grad is correctly propagated through the test model
   @test(testparameters={get_parameters_requires_grad()})
-  subroutine test_tensor_requires_grad(this)
+  subroutine test_output_requires_grad(this)
     use ftorch_tensor, only: torch_tensor_ones, torch_tensor_empty
 
     implicit none
@@ -135,6 +135,6 @@ contains
     ! Check that the output tensor has the correct requires_grad property
     @assertEqual(this%param%requires_grad, output_tensors(1)%requires_grad())
 
-  end subroutine test_tensor_requires_grad
+  end subroutine test_output_requires_grad
 
 end module unittest_model_forward

test/unit/model/unittest_model_interrogation.pf

@@ -69,7 +69,7 @@ contains
 
   ! Unit test for printing the parameters associated with a TorchScript model
   @test(testparameters={get_parameters_short()})
-  subroutine test_torch_model_print_parameters(this)
+  subroutine test_print_parameters(this)
     use ftorch_model, only: torch_model_print_parameters
     class(TestCaseType), intent(inout) :: this
     type(torch_model) :: model
@@ -80,11 +80,11 @@ contains
     ! Check that printing the model parameters doesn't raise an error
     call torch_model_print_parameters(model)
 
-  end subroutine test_torch_model_print_parameters
+  end subroutine test_print_parameters
 
   ! Unit test for checking the default of whether a Torch Model is in training mode
   @test(testparameters={get_parameters_short()})
-  subroutine test_torch_model_is_training_default(this)
+  subroutine test_is_training_default(this)
     class(TestCaseType), intent(inout) :: this
     type(torch_model) :: model
 
@@ -94,11 +94,11 @@ contains
     ! Check that printing the model parameters doesn't raise an error
     @assertFalse(model%is_training())
 
-  end subroutine test_torch_model_is_training_default
+  end subroutine test_is_training_default
 
   ! Unit test for checking whether a Torch Model is in training mode
   @test(testparameters={get_parameters_is_training()})
-  subroutine test_torch_model_is_training(this)
+  subroutine test_is_training(this)
     class(TestCaseType), intent(inout) :: this
     type(torch_model) :: model
 
@@ -108,6 +108,6 @@ contains
     ! Check that printing the model parameters doesn't raise an error
     @assertEqual(this%param%is_training, model%is_training())
 
-  end subroutine test_torch_model_is_training
+  end subroutine test_is_training
 
 end module unittest_model_interrogation

test/unit/tensor/unittest_tensor_autograd.pf

@@ -146,7 +146,7 @@ contains
   end function toString
 
   @test(testParameters={get_parameters_short()})
-  subroutine test_torch_tensor_zero_grad(this)
+  subroutine test_zero_grad(this)
 
     implicit none
 
@@ -174,19 +174,19 @@ contains
     call torch_tensor_backward(Q)
     call torch_tensor_get_gradient(dQda, a)
     expected(:,:) = 1.0
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_zero_grad1"))
+    @assertTrue(allclose(out_data, expected, test_name="test_zero_grad1"))
 
     ! Call torch_tensor_zero_grad and check the gradient is indeed reset to zero. Note that we need
     ! to call torch_tensor_get_gradient again after zeroing out these values.
     call a%zero_grad()
     call torch_tensor_get_gradient(dQda, a)
     expected(:,:) = 0.0
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_zero_grad2"))
+    @assertTrue(allclose(out_data, expected, test_name="test_zero_grad2"))
 
-  end subroutine test_torch_tensor_zero_grad
+  end subroutine test_zero_grad
 
   @test(testParameters={get_parameters_short()})
-  subroutine test_torch_tensor_retain_graph(this)
+  subroutine test_retain_graph(this)
 
     implicit none
 
@@ -214,16 +214,16 @@ contains
     call torch_tensor_backward(Q)
     call torch_tensor_get_gradient(dQda, a)
     expected(:,:) = 1.0
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_retain_graph1"))
+    @assertTrue(allclose(out_data, expected, test_name="test_retain_graph1"))
 
     ! Zero the gradient and then call back-propagation again and check the computed gradient still
     ! takes the expected value
     call a%zero_grad()
     call torch_tensor_backward(Q, retain_graph=.true.)
     call torch_tensor_get_gradient(dQda, a)
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_retain_graph2"))
+    @assertTrue(allclose(out_data, expected, test_name="test_retain_graph2"))
 
-  end subroutine test_torch_tensor_retain_graph
+  end subroutine test_retain_graph
 
   ! ============================================================================
   ! --- Unit tests for the requires_grad property

test/unit/tensor/unittest_tensor_constructors_destructors.pf

@@ -95,7 +95,7 @@ contains
 
   ! Unit test for the torch_tensor_empty subroutine
   @test(testparameters={get_parameters_requires_grad()})
-  subroutine test_torch_tensor_empty(this)
+  subroutine test_empty(this)
     use ftorch_tensor, only: torch_tensor_empty
 
     implicit none
@@ -120,11 +120,11 @@ contains
     @assertEqual(expected_stride, tensor % get_stride())
     @assertEqual(tensor_shape, tensor % get_shape())
 
-  end subroutine test_torch_tensor_empty
+  end subroutine test_empty
 
   ! Unit test for the torch_tensor_zeros subroutine
   @test(testParameters={get_parameters_requires_grad()})
-  subroutine test_torch_tensor_zeros(this)
+  subroutine test_zeros(this)
     use ftorch_tensor, only: torch_tensor_zeros
 
     implicit none
@@ -160,13 +160,13 @@ contains
 
     ! Check that the tensor values are all zero
     expected(:,:) = 0.0
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_zeros"))
+    @assertTrue(allclose(out_data, expected, test_name="test_zeros"))
 
-  end subroutine test_torch_tensor_zeros
+  end subroutine test_zeros
 
   ! Unit test for the torch_tensor_ones subroutine
   @test(testParameters={get_parameters_requires_grad()})
-  subroutine test_torch_tensor_ones(this)
+  subroutine test_ones(this)
     use ftorch_tensor, only: torch_tensor_ones
 
     implicit none
@@ -202,9 +202,9 @@ contains
 
     ! Check that the tensor values are all one
     expected(:,:) = 1.0
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_ones"))
+    @assertTrue(allclose(out_data, expected, test_name="test_ones"))
 
-  end subroutine test_torch_tensor_ones
+  end subroutine test_ones
 
   ! Unit test for the torch_tensor_from_array subroutine in the 1D case
   @test(testParameters={get_parameters_requires_grad()})
@@ -243,7 +243,7 @@ contains
     tensor2 = tensor1
 
     ! Compare the data in the tensor to the input data
-    @assertTrue(allclose(out_data, in_data, test_name="test_torch_tensor_from_array"))
+    @assertTrue(allclose(out_data, in_data, test_name="test_from_array"))
 
   end subroutine test_torch_from_array_1d
 
@@ -295,7 +295,7 @@ contains
 
     ! Compare the data in the tensor to the (reordered) input data
     expected(:,:) = reshape(in_data, [2,3], order=tensor_layout)
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_from_array"))
+    @assertTrue(allclose(out_data, expected, test_name="test_from_array"))
 
   end subroutine test_torch_from_array_2d
 
@@ -347,7 +347,7 @@ contains
 
     ! Compare the data in the tensor to the (reordered) input data
     expected(:,:,:) = reshape(in_data, [1,2,3], order=tensor_layout)
-    @assertTrue(allclose(out_data, expected, test_name="test_torch_tensor_from_array"))
+    @assertTrue(allclose(out_data, expected, test_name="test_from_array"))
 
   end subroutine test_torch_from_array_3d
 
@@ -388,14 +388,14 @@ contains
     tensor2 = tensor1
 
     ! Compare the data in the tensor to the input data
-    @assertTrue(allclose(out_data, in_data, test_name="test_torch_tensor_from_blob"))
+    @assertTrue(allclose(out_data, in_data, test_name="test_from_blob"))
 
   end subroutine test_torch_from_blob
 
   ! Unit test for destroying tensors, both manually with torch_tensor_delete and automatically (via
   ! torch_tensor's destructor)
   @test(testparameters={get_parameters_destruction()})
-  subroutine test_torch_tensor_destruction(this)
+  subroutine test_destruction(this)
     use ftorch_tensor, only: torch_tensor_empty
 
     implicit none
@@ -427,6 +427,6 @@ contains
 
     end do
 
-  end subroutine test_torch_tensor_destruction
+  end subroutine test_destruction
 
 end module unittest_tensor_constructors_destructors

test/unit/tensor/unittest_tensor_interrogation_cuda.pf

@@ -25,7 +25,7 @@ contains
 
   ! Unit test for the torch_tensor_get_device_type function applied to a tensor on a CUDA device
   @test
-  subroutine test_torch_tensor_get_device_type()
+  subroutine test_get_device_type()
 
     implicit none
 
@@ -39,12 +39,12 @@ contains
     call torch_tensor_empty(tensor, ndims, tensor_shape, dtype, device_type)
     @assertEqual(expected, tensor%get_device_type())
 
-  end subroutine test_torch_tensor_get_device_type
+  end subroutine test_get_device_type
 
   ! Unit test for the torch_tensor_get_device_index function applied to a tensor on a CUDA device
   ! Tensor is created without specifying a device_index so should default to device 0
   @test
-  subroutine test_torch_tensor_get_device_index_default()
+  subroutine test_get_device_index_default()
 
     implicit none
 
@@ -58,6 +58,6 @@ contains
     call torch_tensor_empty(tensor, ndims, tensor_shape, dtype, device_type)
     @assertEqual(expected, tensor%get_device_index())
 
-  end subroutine test_torch_tensor_get_device_index_default
+  end subroutine test_get_device_index_default
 
 end module unittest_tensor_interrogation_cuda

test/unit/tensor/unittest_tensor_manipulation.pf

@@ -22,7 +22,7 @@ contains
 
   ! Unit test for the torch_tensor_zero subroutine
   @test
-  subroutine test_torch_tensor_zero()
+  subroutine test_zero()
     use, intrinsic :: iso_fortran_env, only: sp => real32
 
     ! Set working precision for reals
@@ -45,8 +45,8 @@ contains
 
     ! Compare the data in the tensor to the input array
     expected(:,:) = 0.0
-    @assertTrue(allclose(in_data, expected, test_name="test_torch_tensor_zero"))
+    @assertTrue(allclose(in_data, expected, test_name="test_zero"))
 
-  end subroutine test_torch_tensor_zero
+  end subroutine test_zero
 
 end module unittest_tensor_manipulation

test/unit/tensor/unittest_tensor_manipulation_cuda.pf

@@ -22,10 +22,10 @@ contains
   ! Unit test for the torch_tensor_to subroutine moving a tensor from the CPU (Float64) to a CUDA
   ! device (Float32)
   @test
-  subroutine test_torch_tensor_to()
+  subroutine test_to()
     use, intrinsic :: iso_fortran_env, only: sp => real32, dp => real64
 
-    type(torch_tensor) :: cpu_tensor, gpu_tensor, test_tensor
+    type(torch_tensor) :: cpu_tensor, gpu_tensor, temp
     real(dp), dimension(2,3,4) :: dp_data
     real(sp), dimension(2,3,4) :: sp_data_expected, temp_array
     integer, parameter :: device_type_source = torch_kCPU
@@ -55,15 +55,15 @@ contains
     @assertTrue(gpu_tensor%get_rank() == cpu_tensor%get_rank())
 
     ! Temporary torch_tensor for testing created from array to extract underlying values
-    call torch_tensor_from_array(test_tensor, temp_array, device_type_source)
+    call torch_tensor_from_array(temp, temp_array, device_type_source)
 
     ! Move back to CPU for comparison
-    call torch_tensor_to(gpu_tensor, test_tensor)
+    call torch_tensor_to(gpu_tensor, temp)
 
     ! Cast the data cpu_tensor is holding in double precision to single precision to
     ! do the comparison with the data held by gpu_tensor (via temp_array)
-    sp_data_expected = real(dp_data, sp) 
-    if (.not. allclose(temp_array, sp_data_expected, "test_torch_tensor_to")) then
+    sp_data_expected = real(dp_data, sp)
+    if (.not. allclose(temp_array, sp_data_expected, "test_to")) then
       print *, "Error :: incorrect output from torch_tensor_to"
       print *, "Source Tensor:"
       call torch_tensor_print(cpu_tensor)
@@ -72,6 +72,6 @@ contains
       stop 999
     end if
 
-  end subroutine test_torch_tensor_to
+  end subroutine test_to
 
 end module unittest_tensor_manipulation_cuda