ModuleCache working

theano/gof/cc.py

@@ -29,6 +29,7 @@ def info(*args):
     sys.stderr.write('INFO:'+ ' '.join(str(a) for a in args)+'\n')
     _logger.info(' '.join(str(a) for a in args))
 def debug(*args):
+    sys.stderr.write('DEBUG:'+ ' '.join(str(a) for a in args)+'\n')
     _logger.debug(' '.join(str(a) for a in args))
 def warning(*args):
     sys.stderr.write('WARNING:'+ ' '.join(str(a) for a in args)+'\n')
@@ -39,19 +40,14 @@ def error(*args):
 
 from .callcache import CallCache
 
-_timers = {}
-
-_module_cache = None
 def get_module_cache():
-    global _module_cache
-    if _module_cache is None:
-        _module_cache = CallCache() #TODO: put a filename here for persistence
-    return _module_cache
+    return cmodule.get_module_cache(get_compiledir())
+
 _persistent_module_cache = None
 def get_persistent_module_cache():
     global _persistent_module_cache
     if _persistent_module_cache is None:
-        _persistent_module_cache = CallCache() #TODO: put a filename here for persistence
+        _persistent_module_cache = CallCache(os.path.join(get_compiledir(), 'persistent_cache'))
     return _persistent_module_cache
  
 class CodeBlock:
@@ -746,7 +742,29 @@ class CLinker(link.Linker):
         rval = tuple(rval)
         return rval
 
-    def compile_cmodule(self):
+    def compile_cmodule(self, location=None):
+        """
+        This method is a callback for `ModuleCache.module_from_key`
+        """
+        location = get_compiledir() if location is None else location
+        mod = self.build_dynamic_module()
+        get_lock()
+        try:
+            debug("LOCATION", location)
+            module = self.module_compile_str(
+                    module_name=mod.name,
+                    src_code = mod.code(),
+                    location=location,
+                    include_dirs=[],
+                    libs=self.libraries(),
+                    preargs=self.compile_args())
+        finally:
+            release_lock()
+
+        return module
+
+
+    def build_dynamic_module(self):
         """Generate the code for this module, compile it, return the imported dynamic module.
         """
         self.code_gen()
@@ -755,18 +773,7 @@ class CLinker(link.Linker):
         cthunk = object() # dummy so weave can get the type
         mod = cmodule.DynamicModule(module_name)
 
-        if 0:
-            # Eliminate duplicate inputs and outputs from the storage that we will pass to instantiate
-            out_storage = [x for i, x in enumerate(out_storage) if (i+len(in_storage)) not in self.dupidx]
-            in_storage = [x for i, x in enumerate(in_storage) if i not in self.dupidx]
-
-
-            argnames = ["i%i" % i for i in xrange(len(in_storage))] \
-                + ["o%i" % i for i in xrange(len(out_storage))] \
-                + ["orph%i" % i for i in xrange(len(self.orphans))]
-
         # The code of instantiate
-        #code = self.instantiate_code(1+len(argnames)) #the 1 is for error_storage
         code = self.instantiate_code(1+len(self.args)) #the 1 is for error_storage
         instantiate = cmodule.ExtFunction('instantiate', code, method=cmodule.METH_VARARGS)
                 #['error_storage'] + argnames,
@@ -799,19 +806,7 @@ class CLinker(link.Linker):
         for header in self.headers():
             mod.add_include(header)
 
-        get_lock()
-        try:
-            module = self.module_compile_str(
-                    module_name=mod.name,
-                    src_code = mod.code(),
-                    location=get_compiledir(),
-                    include_dirs=[],
-                    libs=self.libraries(),
-                    preargs=self.compile_args())
-        finally:
-            release_lock()
-
-        return module
+        return mod
 
 
     def cthunk_factory(self, error_storage, in_storage, out_storage):
@@ -831,9 +826,10 @@ class CLinker(link.Linker):
         except KeyError:
             key = None
         if key is None:
+            #if we can't get a key, then forget the cache mechanism
             module = self.compile_cmodule()
         else:
-            module = get_module_cache().call(self.compile_cmodule, key=key)
+            module = get_module_cache().module_from_key(key=key, fn=self.compile_cmodule)
 
         vars = self.inputs + self.outputs + self.orphans
         # List of indices that should be ignored when passing the arguments

theano/gof/cmodule.py

 """Generate and compile C modules for Python
 """
-import os, tempfile, StringIO, sys, logging, subprocess
+import os, tempfile, StringIO, sys, logging, subprocess, cPickle, atexit
 
 _logger=logging.getLogger("theano.gof.cmodule")
 
 def warning(*args):
-    sys.stderr.write('WARNING:'+ ' '.join(str(a) for a in args)+'\n')
+    #sys.stderr.write('WARNING:'+ ' '.join(str(a) for a in args)+'\n')
     _logger.warning(' '.join(str(a) for a in args))
 def info(*args):
-    sys.stderr.write('INFO:'+ ' '.join(str(a) for a in args)+'\n')
+    #sys.stderr.write('INFO:'+ ' '.join(str(a) for a in args)+'\n')
     _logger.info(' '.join(str(a) for a in args))
 def debug(*args):
     #sys.stderr.write('DEBUG:'+ ' '.join(str(a) for a in args)+'\n')
@@ -115,10 +115,138 @@ class DynamicModule(object):
 
     #TODO: add_type
 
+def dlimport(fullpath, suffix=None):
+    """Dynamically load a .so, .dll, or .py file
 
+    :type fullpath: string
+    :param fullpath: a fully-qualified path do a compiled python module
+    :param suffix: a suffix to strip from the end of fullpath to get the import name
+    :type suffix: string
+
+    :returns: the dynamically loaded module (from __import__)
+
+    """
+    if suffix is None:
+        if fullpath.endswith('.so'):
+            suffix = '.so'
+        elif fullpath.endswith('.dll'):
+            suffix = '.dll'
+        elif fullpath.endswith('.py'):
+            suffix = '.py'
+        else:
+            suffix = ''
+    rval = None
+    if fullpath.endswith(suffix):
+        module_name = '.'.join(fullpath.split(os.path.sep)[-2:])[:-len(suffix)]
+    else:
+        raise ValueError('path has wrong suffix', (fullpath, suffix))
+    workdir = fullpath[:-len(module_name)- 1 - len(suffix)]
+    #debug("WORKDIR", workdir)
+    #debug("module_name", module_name)
+
+    pathcopy = list(sys.path)
+    sys.path = [workdir]
+    try:
+        rval = __import__(module_name, {}, {}, [module_name])
+        if not rval:
+            error('__import__ failed', fullpath)
+    finally:
+        sys.path = pathcopy
+
+    assert fullpath.startswith(rval.__file__)
+    return rval
+
+class ModuleCache(object):
+    def __init__(self, dirname, force_fresh=False):
+        self.dirname = dirname
+        self.module_from_name = {}
+        self.name_from_key_filename = os.path.join(self.dirname, 'module_cache.pkl')
+        self.name_from_key = {}      
+        self.stats = [0, 0, 0]
+
+        if not force_fresh:
+            try:
+                f = file(self.name_from_key_filename, 'r')
+                self.name_from_key = cPickle.load(f)
+                debug('ModuleCache loaded', len(self.name_from_key))
+                f.close()
+            except (IOError, EOFError):
+                debug('cache load failed. Using fresh cache')
+                pass
+
+    def persist(self):
+        f = file(self.name_from_key_filename, 'w')
+        cPickle.dump(self.name_from_key, f)
+        f.close()
+
+    def module_from_key(self, key, fn=None):
+        rval = None
+        if key in self.name_from_key:
+            # we have seen this key either in this process or previously
+            #debug('OLD KEY HASH', hash(key), hash(key[1][0]), key[1][0])
+            name = self.name_from_key[key]
+
+            if name not in self.module_from_name:
+                #debug('loading name', name)
+                self.module_from_name[name] = dlimport(name)
+                self.stats[1] += 1
+            else:
+                self.stats[0] += 1
+            rval = self.module_from_name[name]
+        else:
+            # we have never seen this key before
+            location = tempfile.mkdtemp(dir=self.dirname)
+            #debug("LOCATION*", location)
+            try:
+                module = fn(location=location)  # WILL FAIL FOR BAD C CODE
+            finally:
+                #   >>TODO: erase location
+                pass 
+
+            debug('NEW KEY HASH', hash(key), hash(key[1][0]), key[1][0])
+            for k,n in self.name_from_key.iteritems():
+                if k == key:
+                    debug("HASH OF RELOAD IS DIFFERENT", hash(k), hash(key))
+                    print ''
+                    print hash(k[0])
+                    print hash(key[0])
+                    print ''
+                    print "OLD",
+                    print hash(k[1][0])
+                    print k[1][0].rehash()
+                    print ""
+                    print "NEW", hash(key[1][0]), key[1][0].rehash()
+                    print ''
+                    print hash(k[1][1])
+                    print hash(key[1][1])
+                    assert k != key
+            name = module.__file__
+            #debug("LOCATION**", location)
+            #debug("NAME**", name)
+            assert name.startswith(location)
+
+            assert name not in self.module_from_name
+            assert key not in self.name_from_key
+            self.name_from_key[key] = name
+            self.module_from_name[name] = module
+
+            self.stats[2] += 1
+            rval = module
+        #debug('stats', self.stats, sum(self.stats))
+        return rval
+
+
+_module_cache = None
+def get_module_cache(dirname):
+    global _module_cache
+    if _module_cache is None:
+        _module_cache = ModuleCache(dirname, force_fresh=False)
+        atexit.register(_module_cache.persist)
+    return _module_cache
 
 def gcc_module_compile_str(module_name, src_code, location=None, include_dirs=[], lib_dirs=[], libs=[],
         preargs=[], tmpdir=None):
+    #TODO: don't to the dlimport in this function
     preargs= [] if preargs is None else list(preargs)
     preargs.append('-fPIC')
     no_opt = False
@@ -127,7 +255,7 @@ def gcc_module_compile_str(module_name, src_code, location=None, include_dirs=[]
     include_dirs = ['/usr/include/python2.6'] + include_dirs
     libs = ['python2.6'] + libs
 
-    workdir = tempfile.mkdtemp(dir=location)
+    workdir = location
 
     cppfilename = os.path.join(workdir, 'mod.cpp')
     cppfile = file(cppfilename, 'w')
@@ -157,19 +285,12 @@ def gcc_module_compile_str(module_name, src_code, location=None, include_dirs=[]
         status = p.wait()
 
         if status:
-            warning('g++ return status', status)
+            error('g++ return status', status)
         else:
             #touch the __init__ file
             file(os.path.join(workdir, "__init__.py"),'w').close()      
 
-            #load the module
-            sys.path.insert(0, workdir)
-            try:
-                rval = __import__(module_name, {}, {}, [module_name])
-                if not rval:
-                    debug('__import__ failed')
-            finally:
-                del sys.path[0]
+            rval = dlimport(lib_filename)
 
     finally:
         warning("TODO: cleanup")
@@ -228,7 +349,6 @@ def nvcc_module_compile_str(module_name, src_code, location=None, include_dirs=[
             file(os.path.join(workdir, "__init__.py"),'w').close()      
 
             #load the module
-            pathcopy = list(sys.path)
             sys.path.insert(0, workdir)
             try:
                 rval = __import__(module_name, {}, {}, [module_name])

theano/gof/op.py

@@ -196,7 +196,7 @@ class PureOp(object):
     variable or an instance variable.
 
     """
-    
+
     #############
     # make_node #
     #############

theano/scalar/basic.py

@@ -59,7 +59,7 @@ class Scalar(Type):
         return type(self) == type(other) and other.dtype == self.dtype
 
     def __hash__(self):
-        return hash(self.dtype)
+        return hash('theano.scalar.Scalar') ^ hash(self.dtype)
 
     def dtype_specs(self):
         try:
@@ -348,7 +348,7 @@ class ScalarOp(Op):
         return test
 
     def __hash__(self):
-        return hash(getattr(self, 'output_types_preference', 0))
+        return hash(type(self).__name__) ^ hash(getattr(self, 'output_types_preference', 0))
 
     def __str__(self):
         if hasattr(self, 'name') and self.name:

theano/tensor/basic.py

@@ -41,6 +41,10 @@ def check_equal_numpy(x, y):
 
 compile.register_checker(check_equal_numpy)
 
+def hashtype(self):
+    t = type(self)
+    return hash(t.__name__) ^ hash(t.__module__)
+elemwise.hashtype = hashtype
 
 
 __oplist_constructor_list = []
@@ -305,7 +309,7 @@ class TensorType(Type):
 
     def __hash__(self):
         """Hash equal for same kinds of TensorType"""
-        return hash(type(self)) ^ hash(self.dtype) ^ hash(self.broadcastable)
+        return hashtype(self) ^ hash(self.dtype) ^ hash(self.broadcastable)
 
     ndim = property(lambda self: len(self.broadcastable), doc = "number of dimensions")
     """Number of dimensions
@@ -732,7 +736,7 @@ class TensorConstantSignature(tuple):
         return (x == a) and (b.shape == y.shape) and (numpy.all(b == y)) 
     def __hash__(self):
         a, b = self
-        return hash(type(self)) ^ hash(a) ^ hash(b.shape)
+        return hashtype(self) ^ hash(a) ^ hash(b.shape)
 
 class TensorConstant(Constant, _tensor_py_operators):
     """Subclass to add the tensor operators to the basic `Constant` class.
@@ -1607,7 +1611,7 @@ class SetSubtensor(Op):
                          if isinstance(entry, slice)
                          else entry
                          for entry in self.idx_list)
-        return hash(type(self)) ^ hash(idx_list) ^ hash(self.inplace)
+        return hashtype(self) ^ hash(idx_list) ^ hash(self.inplace)
 
     def __str__(self):
         indices = []
@@ -2125,7 +2129,7 @@ class Flatten(Op):
     def __eq__(self, other):
         return type(self) == type(other) and self.outdim == other.outdim
     def __hash__(self):
-        return hash(type(self))^hash(self.outdim)
+        return hashtype(self)^hash(self.outdim)
     def make_node(self, x):
         t_x = as_tensor_variable(x)
         if self.outdim < 1 or (x.ndim and self.outdim > x.ndim):
@@ -2277,7 +2281,7 @@ class TensorDotGrad(Op):
         return type(self) == type(other) and self.axes == other.axes
 
     def __hash__(self):
-        return hash(type(self)) ^ hash(self.axes) ^ 89234
+        return hashtype(self) ^ hash(self.axes) ^ 89234
 
     def make_node(self, x, y, gz):
         assert isinstance(x, Variable)
@@ -2324,7 +2328,7 @@ class TensorDot(Op):
         return type(self) == type(other) and self.axes == other.axes
 
     def __hash__(self):
-        return hash(type(self)) ^ hash(self.axes) ^ 89234
+        return hashtype(self) ^ hash(self.axes) ^ 89234
 
     def make_node(self, x, y):
 

theano/tensor/elemwise.py

@@ -123,8 +123,15 @@ class DimShuffle(Op):
         if self.inplace:
             self.view_map = {0: [0]}
 
-        self._hashval = hash(type(self)) ^ hash(self.inplace) \
-                ^ hash(self.new_order) ^ hash(self.input_broadcastable)
+        self._rehash()
+
+    def __getstate__(self):
+        d = dict(self.__dict__)
+        del d['_hashval']
+        return d
+    def __setstate__(self, d):
+        self.__dict__.update(d)
+        self._rehash()
 
     def make_node(self, input):
         ib = tuple(input.type.broadcastable)
@@ -148,6 +155,10 @@ class DimShuffle(Op):
             and self.new_order == other.new_order \
             and self.input_broadcastable == other.input_broadcastable
 
+    def _rehash(self):
+        self._hashval = hash(type(self).__name__) ^ hash(type(self).__module__) ^ hash(self.inplace) \
+                ^ hash(self.new_order) ^ hash(self.input_broadcastable)
+
     def __hash__(self):
         return self._hashval
 
@@ -353,15 +364,13 @@ class Elemwise(Op):
             self.ufunc = None
 
         #precompute the hash of this node
-        items = self.inplace_pattern.items()
-        items.sort()
-        tuple_items = tuple([k for k,v in items] + [(tuple(v) if isinstance(v, (tuple, list)) else v) for k,v in items])
-        self._hashval = hash(self.scalar_op) ^ hash(tuple_items)
+        self._rehash()
 
     def __getstate__(self):
         d = copy(self.__dict__)
         d.pop('ufunc')
         d.pop('__epydoc_asRoutine', None)
+        d.pop('_hashval')
         return d
     
     def __setstate__(self, d):
@@ -370,6 +379,7 @@ class Elemwise(Op):
             self.ufunc = numpy.frompyfunc(self.scalar_op.impl, self.scalar_op.nin, self.scalar_op.nout)
         else:
             self.ufunc = None
+        self._rehash()
 
     def make_node(self, *inputs):
         """
@@ -429,6 +439,14 @@ class Elemwise(Op):
             return rval
         return False
 
+    def _rehash(self):
+        items = self.inplace_pattern.items()
+        items.sort()
+        tuple_items = tuple([k for k,v in items] + [(tuple(v) if isinstance(v, (tuple, list)) else v) for k,v in items])
+        h = hash('Elemwise') ^ hash(self.scalar_op) ^ hash(tuple_items)
+        assert h == getattr(self,'_hashval', h)
+        self._hashval = h
+
     def __hash__(self):
         return self._hashval
 

theano/tensor/nnet.py

@@ -94,6 +94,11 @@ class SoftmaxWithBias(gof.Op):
     def __init__(self, **kwargs):
         gof.Op.__init__(self, **kwargs)
 
+    def __eq__(self, other):
+        return type(self) == type(other)
+    def __hash__(self):
+        return tensor.hashtype(self)
+
     def make_node(self, x, b):
         x = tensor.as_tensor_variable(x)
         b = tensor.as_tensor_variable(b)
@@ -266,8 +271,9 @@ class SoftmaxGrad(gof.Op):
 
     def __eq__(self, other):
         return type(self) == type(other)
+
     def __hash__(self):
-        return hash(type(self))
+        return tensor.hashtype(self)
 
     def make_node(self, dy, sm, **kwargs):
         dy = tensor.as_tensor_variable(dy)
@@ -437,6 +443,10 @@ class CrossentropySoftmaxArgmax1HotWithBias(gof.Op):
     nout=3
     def __init__(self, **kwargs):
         gof.Op.__init__(self, **kwargs)
+    def __eq__(self, other):
+        return type(self) == type(other)
+    def __hash__(self):
+        return tensor.hashtype(self)
 
     def make_node(self, x, b, y_idx):
         x = tensor.as_tensor_variable(x)
@@ -608,6 +618,10 @@ class CrossentropySoftmax1HotWithBiasDx (gof.Op):
     """Gradient wrt x of the CrossentropySoftmax1Hot Op"""
     def __init__(self, **kwargs):
         gof.Op.__init__(self,**kwargs)
+    def __eq__(self, other):
+        return type(self) == type(other)
+    def __hash__(self):
+        return tensor.hashtype(self)
     def make_node(self, dy, sm, y_idx,**kwargs):
         dy = tensor.as_tensor_variable(dy)
         sm = tensor.as_tensor_variable(sm)
@@ -728,7 +742,7 @@ class CrossentropyCategorical1HotGrad(gof.Op):
     def __eq__(self, other):
         return type(self) == type(other)
     def __hash__(self):
-        return hash(type(self))
+        return tensor.hashtype(self)
     def make_node(self, g_y, coding_dist, true_one_of_n):
         return gof.Apply(self, [g_y, coding_dist, true_one_of_n], [coding_dist.type()])
     def perform(self, node, (g_y, coding_dist, true_one_of_n), (g_coding_strg,)):
@@ -741,10 +755,6 @@ crossentropy_categorical_1hot_grad = CrossentropyCategorical1HotGrad()
 
 class CrossentropyCategorical1Hot(gof.Op):
 
-    def __eq__(self, other):
-        return type(self) == type(other)
-    def __hash__(self):
-        return hash(type(self))
     """Compute the cross entropy between a coding distribution and 
     a true distribution of the form [0, 0, ... 0, 1, 0, ..., 0]
 
@@ -758,6 +768,11 @@ class CrossentropyCategorical1Hot(gof.Op):
     Op will probably be optimized away in favour of one with a C implementation.
 
     """
+
+    def __eq__(self, other):
+        return type(self) == type(other)
+    def __hash__(self):
+        return tensor.hashtype(self)
     def make_node(self, coding_dist, true_one_of_n):
         """
         :type coding_dist: dense matrix
@@ -906,6 +921,11 @@ class Prepend_scalar_constant_to_each_row(gof.Op):
             val = scalar.constant(val)
         self.val = val
 
+    def __eq__(self, other):
+        return (type(self) == type(other)) and (self.val == other.val)
+    def __hash__(self):
+        return tensor.hashtype(self) ^ hash(self.val.value)
+
     def make_node(self, mat):
         #check type of input
         if not isinstance(mat,gof.Variable) or not mat.type==tensor.matrix().type:
@@ -938,6 +958,11 @@ class Prepend_scalar_constant_to_each_row(gof.Op):
         return goutput[:,1:]
 
 class Prepend_scalar_to_each_row(gof.Op):
+    def __eq__(self, other):
+        return (type(self) == type(other))
+    def __hash__(self):
+        return tensor.hashtype(self)
+
     def make_node(self, val, mat):
         #check type of input
         if isinstance(val, float):