modifications for 0.X release

HISTORY.txt

@@ -5,6 +5,141 @@
 Release Notes
 =============
 
+Theano 0.4.0 (2011-06-13)
+=========================
+
+Change in output memory storage for Ops:
+ If you implemented custom Ops, with either C or Python implementation,
+ this will concern you.
+
+ The contract for memory storage of Ops has been changed. In particular,
+ it is no longer guaranteed that output memory buffers are either empty,
+ or allocated by a previous execution of the same Op.
+
+ Right now, here is the situation:
+  * For Python implementation (perform), what is inside output_storage
+    may have been allocated from outside the perform() function, for
+    instance by another node (e.g., Scan) or the Mode. If that was the
+    case, the memory can be assumed to be C-contiguous (for the moment).
+  * For C implementations (c_code), nothing has changed yet.
+
+ In a future version, the content of the output storage, both for Python and C
+ versions, will either be NULL, or have the following guarantees:
+  * It will be a Python object of the appropriate Type (for a Tensor variable,
+    a numpy.ndarray, for a GPU variable, a CudaNdarray, for instance)
+  * It will have the correct number of dimensions, and correct dtype
+ However, its shape and memory layout (strides) will not be guaranteed.
+
+ When that change is made, the config flag DebugMode.check_preallocated_output
+ will help you find implementations that are not up-to-date.
+
+Deprecation:
+ * tag.shape attribute deprecated (#633)
+ * CudaNdarray_new_null is deprecated in favour of CudaNdarray_New
+ * Dividing integers with / is deprecated: use // for integer division, or
+   cast one of the integers to a float type if you want a float result (you may
+   also change this behavior with config.int_division).
+ * Removed (already deprecated) sandbox/compile module
+ * Removed (already deprecated) incsubtensor and setsubtensor functions,
+   inc_subtensor and set_subtensor are to be used instead.
+
+Bugs fixed:
+ * In CudaNdarray.__{iadd,idiv}__, when it is not implemented, return the error.
+ * THEANO_FLAGS='optimizer=None' now works as expected
+ * Fixed memory leak in error handling on GPU-to-host copy
+ * Fix relating specifically to Python 2.7 on Mac OS X
+ * infer_shape can now handle Python longs
+ * Trying to compute x % y with one or more arguments being complex now
+   raises an error.
+ * The output of random samples computed with uniform(..., dtype=...) is
+   guaranteed to be of the specified dtype instead of potentially being of a
+   higher-precision dtype.
+ * The perform() method of DownsampleFactorMax did not give the right result
+   when reusing output storage. This happen only if you use the Theano flags 
+   'linker=c|py_nogc' or manually specify the mode to be 'c|py_nogc'.
+
+Crash fixed:
+ * Work around a bug in gcc 4.3.0 that make the compilation of 2d convolution
+   crash.
+ * Some optimizations crashed when the "ShapeOpt" optimization was disabled.
+
+Optimization:
+ * Optimize all subtensor followed by subtensor.
+
+GPU:
+ * Move to the gpu fused elemwise that have other dtype then float32 in them
+   (except float64) if the input and output are float32.
+   * This allow to move elemwise comparisons to the GPU if we cast it to
+     float32 after that.
+ * Implemented CudaNdarray.ndim to have the same interface in ndarray.
+ * Fixed slowdown caused by multiple chained views on CudaNdarray objects
+ * CudaNdarray_alloc_contiguous changed so as to never try to free
+   memory on a view: new "base" property
+ * Safer decref behaviour in CudaNdarray in case of failed allocations
+ * New GPU implementation of tensor.basic.outer
+ * Multinomial random variates now available on GPU
+
+New features:
+ * ProfileMode
+    * profile the scan overhead
+    * simple hook system to add profiler
+    * reordered the output to be in the order of more general to more specific
+ * DebugMode now checks Ops with different patterns of preallocated memory,
+   configured by config.DebugMode.check_preallocated_output.
+ * var[vector of index] now work, (grad work recursively, the direct grad
+   work inplace, gpu work)
+    * limitation: work only of the outer most dimensions.
+ * New way to test the graph as we build it. Allow to easily find the source
+   of shape mismatch error:
+   `http://deeplearning.net/software/theano/tutorial/debug_faq.html#interactive-debugger`__
+ * cuda.root inferred if nvcc is on the path, otherwise defaults to
+   /usr/local/cuda
+ * Better graph printing for graphs involving a scan subgraph
+ * Casting behavior can be controlled through config.cast_policy,
+   new (experimental) mode.
+ * Smarter C module cache, avoiding erroneous usage of the wrong C
+   implementation when some options change, and avoiding recompiling the
+   same module multiple times in some situations.
+ * The "theano-cache clear" command now clears the cache more thoroughly.
+ * More extensive linear algebra ops (CPU only) that wrap scipy.linalg
+   now available in the sandbox.
+ * CUDA devices 4 - 16 should now be available if present.
+ * infer_shape support for the View op, better infer_shape support in Scan
+ * infer_shape supported in all case of subtensor
+ * tensor.grad now gives an error by default when computing the gradient
+   wrt a node that is disconnected from the cost (not in the graph, or
+   no continuous path from that op to the cost).
+ * New tensor.isnan and isinf functions.
+
+Documentation:
+ * Better commenting of cuda_ndarray.cu
+ * Fixes in the scan documentation: add missing declarations/print statements
+ * Better error message on failed __getitem__
+ * Updated documentation on profile mode
+ * Better documentation of testing on Windows
+ * Better documentation of the 'run_individual_tests' script
+
+Unit tests:
+ * More strict float comparaison by default
+ * Reuse test for subtensor of tensor for gpu tensor(more gpu test)
+ * Tests that check for aliased function inputs and assure appropriate copying
+   (#374)
+ * Better test of copies in CudaNdarray
+ * New tests relating to the new base pointer requirements
+ * Better scripts to run tests individually or in batches
+ * Some tests are now run whenever cuda is available and not just when it has
+   been enabled before
+ * Tests display less pointless warnings.
+
+Other:
+ * Correctly put the broadcast flag to True in the output var of
+   a Reshape op when we receive an int 1 in the new shape.
+ * pydotprint: high contrast mode is now the default, option to print
+   more compact node names.
+ * pydotprint: How trunk label that are too long.
+ * More compact printing (ignore leading "Composite" in op names)
+
+
 Theano 0.3.1 (2011-02-21)
 =========================
 

NEWS.txt

-documented all commits up to: a1f5e8f854f8(during 28 july 2011)
-
-Modifications in the 0.4.1 release candidate 1
+Modifications in the 0.4.1 release candidate 1(28 July 2011)
 
 TODO:
  * LazyLinker, VM, CVM with profile
@@ -121,138 +119,3 @@ Core:
    "destroyhandler_tolerate_aliased" then this is what's going on.
    IncSubtensor is thus far the only Op to use this mechanism.Mechanism
 
-
-
-Theano 0.4.0 (2011-06-13)
---------------------------------------------------
-
-Change in output memory storage for Ops:
- If you implemented custom Ops, with either C or Python implementation,
- this will concern you.
-
- The contract for memory storage of Ops has been changed. In particular,
- it is no longer guaranteed that output memory buffers are either empty,
- or allocated by a previous execution of the same Op.
-
- Right now, here is the situation:
-  * For Python implementation (perform), what is inside output_storage
-    may have been allocated from outside the perform() function, for
-    instance by another node (e.g., Scan) or the Mode. If that was the
-    case, the memory can be assumed to be C-contiguous (for the moment).
-  * For C implementations (c_code), nothing has changed yet.
-
- In a future version, the content of the output storage, both for Python and C
- versions, will either be NULL, or have the following guarantees:
-  * It will be a Python object of the appropriate Type (for a Tensor variable,
-    a numpy.ndarray, for a GPU variable, a CudaNdarray, for instance)
-  * It will have the correct number of dimensions, and correct dtype
- However, its shape and memory layout (strides) will not be guaranteed.
-
- When that change is made, the config flag DebugMode.check_preallocated_output
- will help you find implementations that are not up-to-date.
-
-Deprecation:
- * tag.shape attribute deprecated (#633)
- * CudaNdarray_new_null is deprecated in favour of CudaNdarray_New
- * Dividing integers with / is deprecated: use // for integer division, or
-   cast one of the integers to a float type if you want a float result (you may
-   also change this behavior with config.int_division).
- * Removed (already deprecated) sandbox/compile module
- * Removed (already deprecated) incsubtensor and setsubtensor functions,
-   inc_subtensor and set_subtensor are to be used instead.
-
-Bugs fixed:
- * In CudaNdarray.__{iadd,idiv}__, when it is not implemented, return the error.
- * THEANO_FLAGS='optimizer=None' now works as expected
- * Fixed memory leak in error handling on GPU-to-host copy
- * Fix relating specifically to Python 2.7 on Mac OS X
- * infer_shape can now handle Python longs
- * Trying to compute x % y with one or more arguments being complex now
-   raises an error.
- * The output of random samples computed with uniform(..., dtype=...) is
-   guaranteed to be of the specified dtype instead of potentially being of a
-   higher-precision dtype.
- * The perform() method of DownsampleFactorMax did not give the right result
-   when reusing output storage. This happen only if you use the Theano flags 
-   'linker=c|py_nogc' or manually specify the mode to be 'c|py_nogc'.
-
-Crash fixed:
- * Work around a bug in gcc 4.3.0 that make the compilation of 2d convolution
-   crash.
- * Some optimizations crashed when the "ShapeOpt" optimization was disabled.
-
-Optimization:
- * Optimize all subtensor followed by subtensor.
-
-GPU:
- * Move to the gpu fused elemwise that have other dtype then float32 in them
-   (except float64) if the input and output are float32.
-   * This allow to move elemwise comparisons to the GPU if we cast it to
-     float32 after that.
- * Implemented CudaNdarray.ndim to have the same interface in ndarray.
- * Fixed slowdown caused by multiple chained views on CudaNdarray objects
- * CudaNdarray_alloc_contiguous changed so as to never try to free
-   memory on a view: new "base" property
- * Safer decref behaviour in CudaNdarray in case of failed allocations
- * New GPU implementation of tensor.basic.outer
- * Multinomial random variates now available on GPU
-
-New features:
- * ProfileMode
-    * profile the scan overhead
-    * simple hook system to add profiler
-    * reordered the output to be in the order of more general to more specific
- * DebugMode now checks Ops with different patterns of preallocated memory,
-   configured by config.DebugMode.check_preallocated_output.
- * var[vector of index] now work, (grad work recursively, the direct grad
-   work inplace, gpu work)
-    * limitation: work only of the outer most dimensions.
- * New way to test the graph as we build it. Allow to easily find the source
-   of shape mismatch error:
-   `http://deeplearning.net/software/theano/tutorial/debug_faq.html#interactive-debugger`__
- * cuda.root inferred if nvcc is on the path, otherwise defaults to
-   /usr/local/cuda
- * Better graph printing for graphs involving a scan subgraph
- * Casting behavior can be controlled through config.cast_policy,
-   new (experimental) mode.
- * Smarter C module cache, avoiding erroneous usage of the wrong C
-   implementation when some options change, and avoiding recompiling the
-   same module multiple times in some situations.
- * The "theano-cache clear" command now clears the cache more thoroughly.
- * More extensive linear algebra ops (CPU only) that wrap scipy.linalg
-   now available in the sandbox.
- * CUDA devices 4 - 16 should now be available if present.
- * infer_shape support for the View op, better infer_shape support in Scan
- * infer_shape supported in all case of subtensor
- * tensor.grad now gives an error by default when computing the gradient
-   wrt a node that is disconnected from the cost (not in the graph, or
-   no continuous path from that op to the cost).
- * New tensor.isnan and isinf functions.
-
-Documentation:
- * Better commenting of cuda_ndarray.cu
- * Fixes in the scan documentation: add missing declarations/print statements
- * Better error message on failed __getitem__
- * Updated documentation on profile mode
- * Better documentation of testing on Windows
- * Better documentation of the 'run_individual_tests' script
-
-Unit tests:
- * More strict float comparaison by default
- * Reuse test for subtensor of tensor for gpu tensor(more gpu test)
- * Tests that check for aliased function inputs and assure appropriate copying
-   (#374)
- * Better test of copies in CudaNdarray
- * New tests relating to the new base pointer requirements
- * Better scripts to run tests individually or in batches
- * Some tests are now run whenever cuda is available and not just when it has
-   been enabled before
- * Tests display less pointless warnings.
-
-Other:
- * Correctly put the broadcast flag to True in the output var of
-   a Reshape op when we receive an int 1 in the new shape.
- * pydotprint: high contrast mode is now the default, option to print
-   more compact node names.
- * pydotprint: How trunk label that are too long.
- * More compact printing (ignore leading "Composite" in op names)

doc/library/config.txt

@@ -245,7 +245,7 @@ import theano and print the config variable, as in:
 
 .. attribute:: config.warn.ignore_bug_before
 
-    String value: 'None', 'all', '0.3', '0.4'
+    String value: 'None', 'all', '0.3', '0.4', '0.4.1'
 
     Default: 'None'
 

theano/configdefaults.py

@@ -223,7 +223,7 @@ AddConfigVar('numpy.seterr_invalid',
 ###
 AddConfigVar('warn.ignore_bug_before',
              "If 'None', we warn about all Theano bugs found by default. If 'all', we don't warn about Theano bugs found by default. If a version, we print only the warnings relative to Theano bugs found after that version. Warning for specific bugs can be configured with specific [warn] flags.",
-             EnumStr('None', 'all', '0.3','0.4', allow_override=False),
+             EnumStr('None', 'all', '0.3','0.4', '0.4.1',allow_override=False),
              in_c_key=False)
 
 default_0_3 = True