Fix some problems in float16.

[ENH] fix opt error/skip and better error printing.

Correct blocks/threads for gpuarray CorrMM and Corr3DMM

we do it the normal way now.

Doc: Fix library path. Closes #5156.

Number of blocks and number of threads were swapped.

use floatX in gpuarray dnn tests

Pool 2d rename

Add profiling of which node make_thunk take times.

Issue 5008 fixed

Add bool dtype in scalar and tensor.

Fixed typo in config doc

make var() return float16 when input is float16.

Use "PyArray_Transpose" in gemm implementation

Add a test to test_blas.py:TestBlasStrides to check
is gemm works well with non-contiguous matrices
(A,B,C are all passed as non-contiguous).

All tests passed ! Recall: these are the tests executed:

theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestAbstractConvNoOptim
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestBilinearUpsampling
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestCorrConv2d
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestCorrConv3d
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestCpuConv2d
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/nnet/tests/test_abstract_conv.py:TestCpuConv3d
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/tests/test_blas_c.py
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/tests/test_blas.py
theano-cache purge && THEANO_FLAGS=blas.ldflags= nosetests theano/tensor/tests/test_blas_scipy.py
theano-cache purge && THEANO_FLAGS=optdb.max_use_ratio=10,blas.ldflags= nosetests theano/tensor/nnet/tests/test_corr3d.py
theano-cache purge && THEANO_FLAGS=optdb.max_use_ratio=7,blas.ldflags= nosetests theano/tensor/nnet/tests/test_corr.py

Gemm implementation rewritten so that a new data memory
is allocated when we can not reuse C.

C can not be reused either when BETA != 0,
or when BETA == 0 but C is not contiguous
(LDC != M).

All tests passed, + special test suggested by lamblin.

pool.py and test_pool.py respect the flake8 norms. corrections have for the test_pool have been made in order to include more deprecation examples.

Insert GpuSolve only when CULA is available

Doc update about cudnn and cudnn RNN.

Code-comment removed from test_corr.
Code factorized in alt_gemm_template.c

All tests passed.