Python's Theano Learning:

(1) Theano main support symbol matrix expression

(2) Theano and NumPy have broadcasting:numpy in the dynamic, and Theano need to know before this is which dimension needs to be broadcast. Given the following table for different types of data, the base types are scalar, vector, row, col, Matrix, Tensor3, Tensor4, and then the 8, 16, 32, 64 bits corresponding to the shaping int are B, W, I, l The float type corresponds to 32, 64 bits is F, the D;complex type corresponds to 64, 128 bits are C, Z.

Constructor	Dtype	Ndim	Shape	broadcastable
Bscalar	int8	0	()	()
Bvector	int8	1	(?,)	(False,)
Brow	int8	2	(1,?)	(True, False)
Bcol	int8	2	(?, 1)	(False, True)
Bmatrix	int8	2	(?,?)	(False, False)
Btensor3	int8	3	(?,?,?)	(False, False, false)
Btensor4	int8	4	(?,?,?,?)	(False, False, false, false)
Wscalar	Int16	0	()	()
Wvector	Int16	1	(?,)	(False,)
Wrow	Int16	2	(1,?)	(True, False)
Wcol	Int16	2	(?, 1)	(False, True)
Wmatrix	Int16	2	(?,?)	(False, False)
Wtensor3	Int16	3	(?,?,?)	(False, False, false)
Wtensor4	Int16	4	(?,?,?,?)	(False, False, false, false)
Iscalar	Int32	0	()	()
Ivector	Int32	1	(?,)	(False,)
IRow	Int32	2	(1,?)	(True, False)
Icol	Int32	2	(?, 1)	(False, True)
Imatrix	Int32	2	(?,?)	(False, False)
Itensor3	Int32	3	(?,?,?)	(False, False, false)
Itensor4	Int32	4	(?,?,?,?)	(False, False, false, false)
Lscalar	Int64	0	()	()
Lvector	Int64	1	(?,)	(False,)
Lrow	Int64	2	(1,?)	(True, False)
LCol	Int64	2	(?, 1)	(False, True)
Lmatrix	Int64	2	(?,?)	(False, False)
Ltensor3	Int64	3	(?,?,?)	(False, False, false)
Ltensor4	Int64	4	(?,?,?,?)	(False, False, false, false)
Dscalar	Float64	0	()	()
Dvector	Float64	1	(?,)	(False,)
Drow	Float64	2	(1,?)	(True, False)
Dcol	Float64	2	(?, 1)	(False, True)
Dmatrix	Float64	2	(?,?)	(False, False)
Dtensor3	Float64	3	(?,?,?)	(False, False, false)
Dtensor4	Float64	4	(?,?,?,?)	(False, False, false, false)
Fscalar	Float32	0	()	()
Fvector	Float32	1	(?,)	(False,)
Frow	Float32	2	(1,?)	(True, False)
Fcol	Float32	2	(?, 1)	(False, True)
Fmatrix	Float32	2	(?,?)	(False, False)
Ftensor3	Float32	3	(?,?,?)	(False, False, false)
Ftensor4	Float32	4	(?,?,?,?)	(False, False, false, false)
Cscalar	Complex64	0	()	()
Cvector	Complex64	1	(?,)	(False,)
Crow	Complex64	2	(1,?)	(True, False)
Ccol	Complex64	2	(?, 1)	(False, True)
Cmatrix	Complex64	2	(?,?)	(False, False)
Ctensor3	Complex64	3	(?,?,?)	(False, False, false)
Ctensor4	Complex64	4	(?,?,?,?)	(False, False, false, false)
Zscalar	complex128	0	()	()
Zvector	complex128	1	(?,)	(False,)
Zrow	complex128	2	(1,?)	(True, False)
Zcol	complex128	2	(?, 1)	(False, True)
Zmatrix	complex128	2	(?,?)	(False, False)
Ztensor3	complex128	3	(?,?,?)	(False, False, false)
Ztensor4	complex128	4	(?,?,?,?)	(False, False, false, false)

Python's Theano Learning: