diff options
Diffstat (limited to 'test.lua')
-rw-r--r-- | test.lua | 16 |
1 files changed, 8 insertions, 8 deletions
@@ -2923,7 +2923,7 @@ function nntest.View() local target = template:size():totable() local module = nn.View(template:size()) mytester:assertTableEq(module:forward(input):size():totable(), target, "Error in forward (1)") - local module = nn.View(unpack(target)) + local module = nn.View(table.unpack(target)) mytester:assertTableEq(module:forward(input):size():totable(), target, "Error in forward (2)") -- Minibatch @@ -2979,7 +2979,7 @@ function nntest.Reshape() local target = template:size():totable() local module = nn.Reshape(template:size()) mytester:assertTableEq(module:forward(input):size():totable(), target, "Error in forward (1)") - local module = nn.View(unpack(target)) + local module = nn.View(table.unpack(target)) mytester:assertTableEq(module:forward(input):size():totable(), target, "Error in forward (2)") -- Minibatch @@ -3005,7 +3005,7 @@ function nntest.SpatialUpSamplingNearest() end -- Check that the gradient is correct by using finite elements - local input = torch.Tensor(unpack(shape)):zero() + local input = torch.Tensor(table.unpack(shape)):zero() local err = jac.testJacobian(m, input) mytester:assertlt(err, precision, ' error on state ') @@ -3250,7 +3250,7 @@ function nntest.MM() local gradOutput = torch.randn(M, P) local gradInput = mm:backward({A, B}, gradOutput) mytester:assert(#gradInput == 2, 'gradInput must be table of size 2') - local gradA, gradB = unpack(gradInput) + local gradA, gradB = table.unpack(gradInput) mytester:assertTableEq(gradA:size():totable(), A:size():totable(), 'Gradient for input A has wrong size') mytester:assertTableEq(gradB:size():totable(), B:size():totable(), @@ -3281,7 +3281,7 @@ function nntest.BatchMMNoTranspose() local gradOutput = torch.randn(bSize, M, P) local gradInput = mm:backward({A, B}, gradOutput) mytester:assert(#gradInput == 2, 'gradInput must be table of size 2') - local gradA, gradB = unpack(gradInput) + local gradA, gradB = table.unpack(gradInput) mytester:assertTableEq(gradA:size():totable(), A:size():totable(), 'Gradient for input A has wrong size') mytester:assertTableEq(gradB:size():totable(), B:size():totable(), @@ -3315,7 +3315,7 @@ function nntest.BatchMMTransposeA() local gradOutput = torch.randn(bSize, M, P) local gradInput = mm:backward({A, B}, gradOutput) mytester:assert(#gradInput == 2, 'gradInput must be table of size 2') - local gradA, gradB = unpack(gradInput) + local gradA, gradB = table.unpack(gradInput) mytester:assertTableEq(gradA:size():totable(), A:size():totable(), 'Gradient for input A has wrong size') mytester:assertTableEq(gradB:size():totable(), B:size():totable(), @@ -3349,7 +3349,7 @@ function nntest.BatchMMTransposeB() local gradOutput = torch.randn(bSize, M, P) local gradInput = mm:backward({A, B}, gradOutput) mytester:assert(#gradInput == 2, 'gradInput must be table of size 2') - local gradA, gradB = unpack(gradInput) + local gradA, gradB = table.unpack(gradInput) mytester:assertTableEq(gradA:size():totable(), A:size():totable(), 'Gradient for input A has wrong size') mytester:assertTableEq(gradB:size():totable(), B:size():totable(), @@ -3383,7 +3383,7 @@ function nntest.BatchMMTransposeBoth() local gradOutput = torch.randn(bSize, M, P) local gradInput = mm:backward({A, B}, gradOutput) mytester:assert(#gradInput == 2, 'gradInput must be table of size 2') - local gradA, gradB = unpack(gradInput) + local gradA, gradB = table.unpack(gradInput) mytester:assertTableEq(gradA:size():totable(), A:size():totable(), 'Gradient for input A has wrong size') mytester:assertTableEq(gradB:size():totable(), B:size():totable(), |