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NEWS.txt
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......@@ -8,21 +8,21 @@ https://github.com/Theano/Theano/wiki/Devnews
Release Notes
=============
Theano 0.6rc1 (1 October 2012)
==============================
Theano 0.6rc1 (October 1st, 2012)
=================================
Highlight:
* Bug fix, crash fix, CPU and GPU speed up.
* theano_var.eval({other_var:val[,...]} to simplify the usage of Theano (Ian G.)
* New default linker `cvm`. This is the execution engine that tell what op to run in witch order.
It is now implemented in C and enable lazy evaluation of ifelse op.
Highlights:
* Bug fixes, crash fixes, CPU and GPU speed up.
* theano_var.eval({other_var: val[,...]} to simplify the usage of Theano (Ian G.)
* New default linker `cvm`. This is the execution engine that tells what op to run in which order.
It is now implemented in C and enables lazy evaluation of ifelse op.
* Faster theano.function compilation. (Pascal L., Ian G.)
* Big sparse submodule update and documentation of it. (Nicolas Bouchard)
* Use GPU asynchronous functionality (Frederic B.)
* Better Windows support.
Known bug:
* A few crash case that will be fixed by the final release.
* A few crash cases that will be fixed by the final release.
Bug fixes:
* Outputs of Scan nodes could contain corrupted values: some parts of the
......@@ -46,34 +46,34 @@ Bug fixes:
they were not supposed to share. (David W-F)
* Correctly record the GPU device number used when we let the driver select it.
(Frederic B.)
* CAReduce with NaN in inputs don't return the good output. (Pascal L.)
* CAReduce with NaN in inputs did not return the good output. (Pascal L.)
* This is used in tensor.{all,any,max,mean,prod,sum} and in the grad of PermuteRowElements.
* The grad of TensorDot, was returning the wrong shape for some combination of axes.
We now raise NotImplementedError in those cases. (Frederic B.)
* conv2d with subsample >2 returned wrong values. (Pascal L.)
* Fixed when mode==valid, disabled when mode==full
* theano.sparse.CSMGrad op(generated by the grad of CSM) didn't
handle unsorted input correctly and grapdient that are more sparse
then the input. In that case, bad result was returned. But this can
* theano.sparse.CSMGrad op (generated by the grad of CSM) didn't
handle unsorted input correctly and gradient that is sparser
than the input. In that case, a bad result was returned. But this could
happen only when a sparse input of a Theano function was not
sorted. This happen for example with sparse advanted indexing from
sorted. This happens for example with sparse advanced indexing from
scipy. The conclusion is most of time Nan in the graph.
(Yann Dauphin)
* theano.sparse._dot(CSC matrix, dense) optimized version UsmmCSCDense didn't handled
* theano.sparse._dot(CSC matrix, dense) optimized version UsmmCSCDense didn't handle
correctly not contiguous inputs/outputs. (Pascal L.)
* Fix a corner case CVM updates case. (Pascal L.)
This happen is the update to a shared variable is itself after optimization.
This happened if the update to a shared variable is itself after optimization.
The CVM was not used by default.
* Fix the view_map of sparse.Transpose and sparse.sandbow.sp.RowScale. (Frederic B.)
This probably didn't cause problem as there is only the UsmmCscDense op
(used call to Usmm wieh CSC matrix) that could interfere with them.
(used call to Usmm with CSC matrix) that could interfere with them.
Deprecation:
* Deprecated the Module class (Ian G.)
This was a predecessor of SharedVariable with a less pythonic phylosophy.
This was a predecessor of SharedVariable with a less pythonic philosophy.
Interface changes:
* Now the base version requirement are numpy >= 1.5.0 and the optional scipy >= 0.8.
* Now the base version requirements are numpy >= 1.5.0 and the optional scipy >= 0.8.
* In Theano 0.5, we removed the deprecated sharedvar.value property.
Now we raise an error if you access it. (Frederic B.)
* theano.function does not accept duplicate inputs, so function([x, x], ...)
......@@ -83,7 +83,7 @@ Interface changes:
instance, function([x, y], [y]). You can use the kwarg
``on_unused_input={'raise', 'warn', 'ignore'}`` to control this.
(Pascal L.)
* New Theano flag "on_unused_input" that define the default value of the
* New Theano flag "on_unused_input" that defines the default value of the
previous point. (Frederic B.)
* tensor.alloc() now raises an error during graph build time
when we try to create less dimensions than the number of dimensions
......@@ -96,34 +96,34 @@ Interface changes:
* Renamed the FunctionGraph.nodes attribute to FunctionNodes.apply_nodes (Ian G.)
* Warn when we don't handle correctly the parameter in Theano flags `nvcc.flags`
(Frederic B.)
* Do not reorder the user flags passed to the compiler. They get set after other flags.(Frederic B.)
* Make setuptools optional (Ilan Schnell+)/Remove Dependency.
* We warn when a user try to use an old GPU what we don't test with.
* Do not reorder the user flags passed to the compiler. They get set after other flags. (Frederic B.)
* Make setuptools optional (Ilan Schnell)
* We warn when a user tries to use an old GPU with which TheNo is untested.
This could cause crash and will also be very slow. (Frederic B.)
* Make theano.grad able to differentiate between not implemented, undefined and disconnected grad.
Op.grad function should return theano.gradient.{grad_not_implemented,grad_undefined} or
something of DisconectedType (Ian G.)
* Make theano.grad expect to always receive a float or undefined
gradient and inforce that op with integers output values always
gradient and enforce that op with integer output values always
return 0. (Ian G.)
New memory output contract(was told about in the release note of Theano 0.5):
New memory output contract (was mentioned in the release notes of Theano 0.5):
* Now the output memory received can be preallocated by other stuff.
In the past it was always the previous output an Apply node allowcated.
So this mean that the shape and strides can be different the from previous call
and there can be link to this memory at other place.
This mean it could receive preallocated output that is not c_contiguous.
In the past it was always the previous output an Apply node allocated.
So this means that the shape and strides can be different from previous calls
and there can be links to this memory at other places.
This means it could receive preallocated output that is not c_contiguous.
But we don't do that now. (Pascal L.)
* New Theano flags to test this DebugMode.check_preallocated_output (Pascal L.)
* Updated the a few ops to respect this contract (Pascal L.)
* Updated a few ops to respect this contract (Pascal L.)
New Features:
* GPU scan now work (don't crash) when there is a mixture of float32 and other dtypes.
* GPU scan now works (does not crash) when there is a mixture of float32 and other dtypes.
* theano_var.eval({other_var:val[,...]} to simplify the usage of Theano (Ian G.)
* debugprint new param ids=["CHAR", "id", "int", ""]
This makes the identifier printed to be the python id, a unique char, a
This makes the identifier printed to be a unique char, the Python id, a
unique int, or not have it printed. We changed the default to be "CHAR"
as this is more readable. (Frederic B.)
* debugprint new param stop_on_name=[False, True]. If True, we don't print
......@@ -149,87 +149,87 @@ New Features:
* C code reuses preallocated outputs (only done by Scan) (Pascal L.)
* Garbage collection of intermediate results during Theano function calls
for Ops with C code (Pascal L.)
* Theano flags compiledir_format now support the parameter "numpy_version" and "g++". (Frederic B.)
* Theano GPU variables, shared variable and constant now support <, <=,
> and >= as as those not on the GPU.
* AdvancedIncSubtensor now support the set_instead_of_inc parameter. (Eric L.)
* Theano flag compiledir_format now supports the parameter "numpy_version" and "g++". (Frederic B.)
* Theano GPU variables, shared variables and constants now support <, <=,
> and >= similar to those not on the GPU.
* AdvancedIncSubtensor now supports the set_instead_of_inc parameter. (Eric L.)
* Added Advanced Indexing support to inc_subtensor and set_subtensor. (Eric L.)
* theano.tensor.{any,all,std,var,mean,prod,sum,argmin,argmax,min,max,max_and_argman}
have a new parameter keepdims (Eric L.)
This allow to broadcast it correctly again the input data to normalize it.
* The Updates object now check that the key are SharedVariable when we pass them
This allows to broadcast it correctly against the input data to normalize it.
* The Updates objects now check that the keys are SharedVariable when we pass them
in the __init__ function. (Pascal L.)
* Set a Theano Variable name on transposed op when the input have one (Frederic B).
* The cvm linker now support garbage collection (enabled by default). (James B. Arnaud B., Pascal L.)
* Set a Theano Variable name on transposed op when the input has one (Frederic B).
* The cvm linker now supports garbage collection (enabled by default). (James B. Arnaud B., Pascal L.)
* The cvm linker is now the default linker.
This make the "loop" around the execution of apply node in C. So this lower the overhead.
This makes the "loop" around the execution of apply node in C. So this lowers the overhead.
* theano_variable[numpy.newaxis] is now supported (James B.)
* Enable ifelse on the GPU. (Frederic B.)
* Correctly support numpy.memmap everywhere (Pascal L.)
We add partial support for them before. Just use the normal tensor operation
on them and it should work.
But take care to don't exhaust your computer memory! (we always generate normal ndarray)
* Add an optimization that stabilize log(softmax(x)). (Ian G.)
But be careful not to exhaust your computer memory! (we always generate normal ndarray)
* Add an optimization that stabilizes log(softmax(x)). (Ian G.)
* Re-enable the Images2Neibs grad. It was not broken, the problem was how we tested it. (Frederic B.)
* If `theano_fn.trust_input` is set to False, do not check if the input are good
* If `theano_fn.trust_input` is set to False, do not check if the inputs are good
when calling the theano function. (Frederic B.)
* Add theano.tensor.blas,gem{m,v} as shortcut.
* theano.grad(..., add_names=True). False for the old
behavior. Otherwise it tries to name the grad variables. (Ian G.)
* theano-nose (Pascal L.)
A wrapper around nosetests that add needed extension.
* --profile-time option, print time spend in each tests (Eric L.)
* --batch option, allow to run tests in batch to lower memory requirement.
A wrapper around nosetests that adds needed extensions.
* --profile-time option, to print time spent in each test (Eric L.)
* --batch option, to allow to run tests in batch to lower memory requirement.
* m = mean(log(1 - sigm(x)))
x - scalar * theano.grad(m, x)
There is a stabilization optimization for this.
Now it is applied more frequently. (Pascal L.)
New Op/function:
New Op/functions:
* Added element-wise operation theano.tensor.{GammaLn,Psi} (John Salvatier, Nicolas Bouchard)
* Added element-wise operation theano.tensor.{arcsin,arctan,arccosh,arcsinh,arctanh,exp2,arctan2} (Nicolas Bouchard)
* Added element-wise operation theano.tensor.{gamma,conj,complex_from_polar,expm1,deg2rad,rad2deg,trunc,gamma} (Nicolas Bouchard)
* Added theano.tensor.argsort that wraps numpy.argsort (Hani Almousli).
* Added theano.tensor.diff that wrap numpy.diff (Nicolas B.)
* Added theano.tensor.bincount that wrap numpy.bincount (Nicolas B., Pascal L, Frederic B.)
* Added theano.tensor.diff that wraps numpy.diff (Nicolas B.)
* Added theano.tensor.bincount that wraps numpy.bincount (Nicolas B., Pascal L, Frederic B.)
* Added theano.tensor.squeeze (Nicolas B.)
This remove broadcasted dimensions from the variable.
Theano-nesque version of numpy.squeeze.
* Added theano.tensor.repeat that wrap numpy.repeat (Nicolas B. + PL)
* Added theano.tensor.bartlett that wrap numpy.bartlett (Eric L.)
* Added theano.tensor.fill_diagonal that wrap numpy.fill_diagonal (Eric L., Frederic B.)
This removes broadcasted dimensions from the variable.
Theano-esque version of numpy.squeeze.
* Added theano.tensor.repeat that wraps numpy.repeat (Nicolas B. + PL)
* Added theano.tensor.bartlett that wraps numpy.bartlett (Eric L.)
* Added theano.tensor.fill_diagonal that wraps numpy.fill_diagonal (Eric L., Frederic B.)
* Added tensor.square that is an alias for tensor.sqr as NumPy (Ian G.)
* Added theano.tensor.load(path, dtype, broadcastable, mmap_mode=None) op
that allow to load a .npy file in a theano graph (Matthew Rocklin)
that allows to load a .npy file in a theano graph (Matthew Rocklin)
* theano.sandbox.linalg.kron.py:Kron op. (Eric L.)
Kronecker product
Speed up:
* CPU convolution are now parallelized (Frederic B.)
By default use all cores/hyper-threads
* CPU convolutions are now parallelized (Frederic B.)
By default use all cores/hyper-threads.
To control it, use the `OMP_NUM_THREADS=N` environment variable where N is the number of
parallel thread to use. By default it is equal to the number of CPU cores/hyper
parallel threads to use. By default it is equal to the number of CPU cores/hyper
threads that you have.
There is a new Theano flags `openmp` to allow/disallow openmp op.
If you BLAS library is parallelized, this flag won't affect it, but the
There is a new Theano flag `openmp` to allow/disallow openmp op.
If your BLAS library is parallelized, this flag won't affect it, but the
env variable will.
* Remove a corner case where du duplicated dot22/gemm in the graph. (Frederic B., Ian G.)
* Enable fusion of elemwise that have the same clients multiple time. (Frederic B.)
* Remove a corner case causing duplicated dot22/gemm in the graph. (Frederic B., Ian G.)
* Enable fusion of elemwise that have the same clients multiple times. (Frederic B.)
* New optimization: Remove reduction over broadcastable dimensions (James B., Frederic B.)
* Faster theano.function compilation. (Pascal L., Ian G.)
* Remove GPU transfer around specify_shape op. (Frederic B.)
* Implemented/tested MANY op.infer_shape method (Eric Larsen)
This allow Theano to make better shape inferance.
This allows Theano to make better shape inferance.
* Implement Solve.infer_shape (Matthew Rocklin)
* Scan memory optimization now work more frequently. (Razvan P.)
There was warning printed by the subtensor optimization in those cases.
* faster rng_mrg python code. (mostly used for tests) (Frederic B.)
* Scan memory optimizations now work more frequently. (Razvan P.)
There was a warning printed by the subtensor optimization in those cases.
* Faster rng_mrg Python code. (mostly used for tests) (Frederic B.)
Speed up GPU:
* Convolution on the GPU now check the generation of the card to make
* Convolution on the GPU now checks the generation of the card to make
it faster in some cases (especially medium/big ouput image) (Frederic B.)
* We had hardcoded 512 as the maximum number of thread per block. Newer card
* We had hardcoded 512 as the maximum number of threads per block. Newer cards
support up to 1024 threads per block.
* Faster GpuAdvancedSubtensor1, GpuSubtensor, GpuAlloc (Frederic B.)
* We now pass the GPU architecture to nvcc when compiling (Frederic B.)
......@@ -237,7 +237,7 @@ Speed up GPU:
Set the environment variable `CUDA_LAUNCH_BLOCKING` to `1` to disable this
for profiling or debugging.
* Faster creation of CudaNdarray objects (Frederic B.)
* Now some Max reduction are implemented on the GPU. (Ian G.)
* Now some Max reductions are implemented on the GPU. (Ian G.)
Sparse Sandbox graduate (moved from theano.sparse.sandbox.sp):
* sparse.remove0 (Frederic B., Nicolas B.)
......@@ -254,21 +254,21 @@ Sparse:
* New Ops: sparse.{sqrt,sqr,log1p,floor,ceil,sgn,round_half_to_even} (Nicolas B.)
* New Ops: sparse.{arctanh,tanh,arcsinh,sinh,arctan,arcsin,tan,sin} (Nicolas B.)
* New functions: structured_{add,exp,log,pow,minimum,maximum,sigmoid} (Yann D., Nicolas B.)
* Op optimized op: StructuredAddSV, StrucutedAddSVCSR (inserted automatically)
* Optimized op: StructuredAddSV, StrucutedAddSVCSR (inserted automatically)
* New Op: sparse.mul_s_v multiplication of sparse matrix by broadcasted vector (Yann D.)
* New Op: sparse.Cast() (Yann D., Nicolas B.)
* Add sparse_variable.astype() and theano.sparse.cast() and
theano.sparse.{b,w,i,l,f,d,c,z}cast() as there tensor equivalent (Nicolas B.)
theano.sparse.{b,w,i,l,f,d,c,z}cast() as their tensor equivalent (Nicolas B.)
* Op class: SamplingDot (Yann D., Nicolas B.)
* Optimized version: SamplingDotCsr, StructuredDotCSC
* Optimization to inster the optimizer version: local_sampling_dot_csr, local_structured_add_s_v
* New Ops: sparse.{Multinomial,Poisson,Binomial}(Yann D., NB)
* Optimizations to insert the optimized version: local_sampling_dot_csr, local_structured_add_s_v
* New Ops: sparse.{Multinomial,Poisson,Binomial} (Yann D., NB)
* Implement the CSMProperties grad method (Yann Dauphin)
* Move optimizations to theano/sparse/opt.py (Nicolas B.)
New flags:
* `profile=True` flag now print a printing of the sum of all printed profile.(Frederic B.)
* It work with the linker vm/cvm(default).
* `profile=True` flag now prints the sum of all printed profiles. (Frederic B.)
* It works with the linkers vm/cvm (default).
* Also print compile time, optimizer time and linker time.
* Also print a summary by op class.
* new flag "profile_optimizer" (Frederic B.)
......@@ -282,14 +282,14 @@ New flags:
if True, will print compilation warning.
* new flag `allow_gc` (Frederic B.)
When False, do not garbage collect intermediate results when they are not needed.
This use more memory, but allocate memory less frequently so faster.
This uses more memory, but allocates memory less frequently so faster.
* new flag `vm.lazy` (Frederic B.)
Useful only for the vm linkers. When lazy is None,
auto detect if lazy evaluation is needed and use the apropriate
version. If lazy it True/False, force the version used between
version. If lazy is True/False, force the version used between
Loop/LoopGC and Stack.
* new flag `cxx`. This is the c++ compiler to use. If empty do not compile c code. (Frederic B.)
* New flag `print_active_device` flag that default to True. (Matthew R.)
* new flag `cxx`. This is the C++ compiler to use. If empty do not compile C code. (Frederic B.)
* New flag `print_active_device` that defaults to True. (Matthew R.)
Documentation:
* Added in the tutorial documentation on how to extend Theano.
......@@ -303,11 +303,11 @@ Documentation:
http://www.deeplearning.net/software/theano/tutorial/sparse.html
* Installation documentation for CentOS6 (Frederic B.)
* Installation documentation for Ubuntu (with GPU) (Frederic B., Matthias Zoehrer)
* Doc type fix, Doc update, Better error messag: Olivier D., David W.F., Frederic B., James B., Matthew Rocklin, Ian G.
* Python Memory Management (Steven Pigeon, Olivier D.)
* Doc typo fixes, Doc updates, Better error messages: Olivier D., David W.F., Frederic B., James B., Matthew Rocklin, Ian G.
* Python Memory Management tutorial (Steven Pigeon, Olivier D.)
Proposal:
* Math framework for complex gradien (Pascal L.)
* Math framework for complex gradients (Pascal L.)
Internal changes:
......@@ -324,25 +324,25 @@ Internal changes:
* tensor.utils.shape_of_variables (Matthew R.)
* Add the numpy abi version and g++/nvcc version in the key of compiled code. (Frederic B.)
* env.replace_all_validate_remove (Frederic B.)
This allow global optimizer to ensure it removed some nodes from the graph.
This is a generic way to catch error that would otherwise duplicate
This allows global optimizer to ensure it removed some nodes from the graph.
This is a generic way to catch errors that would otherwise duplicate
computation.
* It was used for GEMM and Scan optimization (Frederic B., Razvan P.)
* Fix how exception are raised in GPU code (James B.)
* Made code respect pep8: OD, Fred, Pascal L., Nicolas Bouchard, Eric Larsen and others.
* TensorType and CudaNdarrayType now have a value_zeros method that call CudaNdarray.zeros or
numpy.zeros with the right dtype. (Pascal L., Olivier D.)
This allow to have the same code work with both type.
This allows to have the same code work with both types.
* Renamed FunctionGraph.extend function to FunctionGraph.attach_feature. (Ian G.)
* New exception MissingGXX when we try to compile but there is no cxx compiler. (Frederic B.)
* New fct theano.gof.utils.give_variables_names(...) that give unique name to variable. (Matthew R.)
* New fct theano.gof.utils.give_variables_names(...) that gives unique names to variables. (Matthew R.)
* Use most of the time the new NumPy C-API for later NumPy release. (Frederic B.)
* New theano.gof.sched.sort_apply_nodes() that will allow other execution ordering. (Matthew R.)
* New attribute sort_schedule_fn, a way to specify a scheduler to use. (Matthew R.)
Crash Fix:
* Fix import conflict name (usaar33, Frederic B.)
* This make Theano work with PiCloud.
* This makes Theano work with PiCloud.
* Do not try to use the BLAS library when blas.ldflags is manually set to an
empty string (Frederic B., Pascal L.)
* When importing theano on a computer without GPU with the Theano
......@@ -369,7 +369,7 @@ Crash Fix:
* In advanced indexing, if some inputs are constant, no need to call constant(...)
on their value any more. (Pascal L., reported by John Salvatier)
* Fix crash on GPU when the GpuSubtensor didn't put the right stride
when the results tensor had a dimensions with size of 1. (Pascal L,
when the result tensor had a dimension with size of 1. (Pascal L,
reported Graham T.)
* Fix scan crash that made it not run on the GPU in one case. (Guillaume D.)
* If you grad again a random state, don't crash (Razvan P.)
......@@ -379,20 +379,20 @@ Crash Fix:
(Olivier D.)
* Crash fix on python 2.4 with slicing. (Pascal L.)
* grad of argmin and argmax (Razvan P.)
* Don't compute the Rop for shared variable with updates(mostly random).
* Don't compute the Rop for shared variables with updates (mostly random).
We don't use them and they caused crash. (Razvan P.)
* MaxArgmax.grad() when one of the gradient it receive is None. (Razvan P, reported by Mark Fenner)
* MaxArgmax.grad() when one of the gradient it receives is None. (Razvan P, reported by Mark Fenner)
* Fix crash of GpuSum when some dimensions shape was 0. (Frederic B.)
Tests:
* Use less memory (Olivier D.)(frix crash on 32-bits computers)
* Use less memory (Olivier D.) (fix crash on 32-bit computers)
* Fix test with Theano flag "blas.ldflags=". (Frederic B., Pascal L.)
* Fix crash with advanced subtensor and numpy constant.
* Fix random tests crash due to random value. (Pascal L.)
* Always introduce Alloc node when calling alloc and let the optimizer remove them if needed.
This allow DebugMode to catch some shape error. (Pascal L.)
* DebugMode now check the view_map for all type of Theano variable.
It was doing only variable of tensor type. (Frederic B.)
This allows DebugMode to catch some shape error. (Pascal L.)
* DebugMode now checks the view_map for all types of Theano variables.
It was doing only variables of tensor type. (Frederic B.)
Others:
* Remove python warning for some python version. (Gabe Schwartz)
......@@ -401,7 +401,7 @@ Others:
* Now we use http://travis-ci.org/ to run all CPU tests (without SciPy)
with the default mode on all Pull Requests.
This should make the trunk more stable. (Fredric B.)
* Our nightly buildbot now check on python 2.4(Frederic B.)
* Our nightly buildbot now checks on python 2.4 (Frederic B.)
This should make the trunk work on it more frequently.
Other thanks:
......
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