* Theano with GPU works in some cases on Windows now. Still experimental. (Sebastian Urban)
* See the Interface changes.
Interface Behavior Change (was deprecated and generated a warning since Theano 0.3 released the 23 Nov 2010):
* The current default value of the parameter axis of
theano.{max,min,argmax,argmin,max_and_argmax} is now the same as
numpy: None. i.e. operate on all dimensions of the tensor.
numpy: None. i.e. operate on all dimensions of the tensor. (Frédéric Bastien, Olivier Delalleau)
Interface Feature Removed (was deprecated):
* The string mode FAST_RUN_NOGC and STABILIZE are not accepted. It was accepted only by theano.function(). Use Mode(linker='c|py_nogc') or Mode(optimizer='stabilize') instead.
* tensor.grad(cost, wrt) now return an object of the "same type" as wrt
(list/tuple/TensorVariable).
* a few tag.shape and Join.vec_length left.
* tensor.grad(cost, wrt) now return an object of the "same type" as wrt
* a few tag.shape and Join.vec_length left have been removed. (Frederic)
* scan interface change: RP
* scan interface change: (Razvan Pascanu)
* The use of `return_steps` for specifying how many entries of the output
to return has been deprecated. Instead, apply a subtensor to the output
returned by scan to select a certain slice
to return has been removed. Instead, apply a subtensor to the output
returned by scan to select a certain slice.
* The inner function (that scan receives) should return its outputs and
updates following this order:
[outputs], [updates], [condition]. One can skip any of the three if not
used, but the order has to stay unchanged.
* shared.value is moved, use shared.set_value() or shared.get_value() instead.
* shared.value is moved, use shared.set_value() or shared.get_value() instead. (Olivier D.)
New deprecation (will be removed in Theano 0.6, warning generated if you use them):
* tensor.shared() renamed to tensor._shared (Olivier D.) You probably want to call theano.shared()!
Interface bug fixes:
* Rop in some case should have returned a list of one theano variable, but returned the variable itself. (Razvan)
* Theano flags "home" is not used anymore as it was a duplicate. If you use it, theano should raise an error. (Olivier D.)
Interface bug fixes:
* Rop in some case should have returned a list of one theano variable, but returned the variable itself.
* Theano flags "home" is not used anymore as it was a duplicate. If you use it, theano should raise an error.
New deprecation (will be removed in Theano 0.6, warning generated if you use them):
* tensor.shared() renamed to tensor._shared. You probably want to call theano.shared()! (Olivier D.)
New features:
* adding 1d advanced indexing support to inc_subtensor and set_subtensor (James)
* tensor.{zeros,ones}_like now support the dtype param as numpy (Fred)
* config flags "exception_verbosity" to control the verbosity of exceptions (Ian)
* theano-cache list: list the content of the theano cache (Fred)
* tensor.ceil_int_div FB
* MaxAndArgMax.grad now work with any axis(The op support only 1 axis) FB
* Adding 1d advanced indexing support to inc_subtensor and set_subtensor (James Bergstra)
* tensor.{zeros,ones}_like now support the dtype param as numpy (Frederic)
* Added configuration flag "exception_verbosity" to control the verbosity of exceptions (Ian)
* theano-cache list: list the content of the theano cache (Frederic)
* theano-cache unlock: remove the Theano lock (Olivier)
* tensor.ceil_int_div (Frederic)
* MaxAndArgMax.grad now work with any axis(The op support only 1 axis) (Frederic)
* used by tensor.{max,min,max_and_argmax}
* tensor.{all,any} RP
* tensor.roll as numpy: (Matthew Rocklin, DWF)
* Theano works in some cases on Windows now. Still experimental. (Sebastian Urban)
* tensor.{all,any} (Razvan)
* tensor.roll as numpy: (Matthew Rocklin, David Warde-Farley)
* Theano with GPU works in some cases on Windows now. Still experimental. (Sebastian Urban)
* IfElse now allow to have a list/tuple as the result of the if/else branches.
* They must have the same length and correspondig type) RP
* argmax dtype as int64. OD
* added arccos IG
* sparse dot with full output. (Yann Dauphin)
* Optimized to Usmm and UsmmCscDense in some case (YD)
* Note: theano.dot, sparse.dot return a structured_dot grad(
* They must have the same length and corresponding type) (Razvan)
* Argmax output dtype now int64. (Olivier)
* Added the element-wise operation arccos. (Ian)
* sparse dot with full grad output. (Yann Dauphin)
* Optimized to Usmm and UsmmCscDense in some case (Yann)
* Note: theano.dot, sparse.dot return a structured_dot grad.
This mean that the old grad returned a grad value with the same sparsity pattern then the inputs.
* GpuAdvancedSubtensor1 support broadcasted dimensions. (Frederic)
New optimizations:
* AdvancedSubtensor1 reuse preallocated memory if available(scan, c|py_nogc linker)(Fred)
* tensor_variable.size (as numpy) product of the shape elements OD
* sparse_variable.size (as scipy) the number of stored value.OD
* dot22, dot22scalar work with complex(Fred)
* Doc how to wrap in Theano an existing python function(in numpy, scipy, ...) Fred
* Generate Gemv/Gemm more often JB
* remove scan when all computations can be moved outside the loop RP
* scan optimization done earlier. This allow other optimization to be applied FB, RP, GD
* exp(x) * sigmoid(-x) is now correctly optimized to a more stable form.
GPU:
* GpuAdvancedSubtensor1 support broadcasted dimensions
Bug fixes that change results:
* On cpu, if the convolution had received explicit shape information, they where not checked at runtime. This caused wrong result if the input shape was not the one expected. (Fred, reported by Sander Dieleman)
* Scan grad when the input of scan has sequence of different length. (RP reported by Michael Forbes)
* Scan.infer_shape now work correctly when working with a condition for the number of loop. In the past, it returned n_steps as the shape, which is not always true. RP
* Theoretical bug: in some case we could have GPUSum return bad value. Was not able to produce the error..
* AdvancedSubtensor1 reuse preallocated memory if available(scan, c|py_nogc linker)(Frederic)
* tensor_variable.size (as numpy) product of the shape elements. (Olivier)
* sparse_variable.size (as scipy) the number of stored value. (Olivier)
* dot22, dot22scalar work with complex. (Frederic)
* Generate Gemv/Gemm more often. (James)
* remove scan when all computations can be moved outside the loop. (Razvan)
* scan optimization done earlier. This allow other optimization to be applied. (Frederic, Guillaume, Razvan)
* exp(x) * sigmoid(-x) is now correctly optimized to a more stable form. (Olivier)
