Use the new name for op context (which is params now).

theano/sandbox/gpuarray/basic_ops.py

@@ -169,7 +169,7 @@ class Kernel(object):
 
 
 class GpuKernelBase(object):
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def gpu_kernels(self, node, name):
         """
@@ -214,7 +214,7 @@ class GpuKernelBase(object):
 
     def c_support_code_apply(self, node, name):
         kernels = self.gpu_kernels(node, name)
-        ctx = self.get_context(node)
+        ctx = self.get_params(node)
         bins = '\n'.join(self._generate_kernel_bin(k, ctx) for k in kernels)
         codes = '\n'.join(self._generate_kernel_code(k) for k in kernels)
         return '\n'.join([bins, codes])
@@ -248,7 +248,7 @@ class GpuKernelBase(object):
             flags=k._get_c_flags(), fail=fail, ctx=ctx)
 
     def c_init_code_struct(self, node, name, sub):
-        ctx = sub['context']
+        ctx = sub['params']
         kernels = self.gpu_kernels(node, name)
         inits_0 = '\n'.join(self._generate_zeros(k) for k in kernels)
         inits = '\n'.join(self._generate_kernel_init(k, sub['fail'], ctx)
@@ -269,7 +269,7 @@ class GpuKernelBase(object):
         return (self.c_code_cache_version(), self.kernel_version(node))
 
     def kernel_version(self, node):
-        return (3, node.get_context().bin_id)
+        return (3, self.get_params(node).bin_id)
 
 
 class HostFromGpu(Op):
@@ -351,7 +351,7 @@ host_from_gpu = HostFromGpu()
 class GpuFromHost(Op):
     __props__ = ('context_name',)
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def __init__(self, context_name):
         self.context_name = context_name
@@ -366,7 +366,7 @@ class GpuFromHost(Op):
                                               context_name=self.context_name,
                                               dtype=x.dtype)()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return get_context(self.context_name)
 
     def perform(self, node, inp, out, ctx):
@@ -404,7 +404,7 @@ class GpuFromHost(Op):
         if (%(out)s == NULL) {
             %(fail)s
         }
-        """ % {'name': name, 'inp': inputs[0], 'ctx': sub['context'],
+        """ % {'name': name, 'inp': inputs[0], 'ctx': sub['params'],
                'out': outputs[0], 'fail': sub['fail']}
 
     def c_code_cache_version(self):
@@ -414,7 +414,7 @@ class GpuFromHost(Op):
 class GpuToGpu(Op):
     __props__ = ('context_name',)
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def __init__(self, context_name):
         self.context_name = context_name
@@ -429,7 +429,7 @@ class GpuToGpu(Op):
                                               context_name=self.context_name,
                                               dtype=x.dtype)()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return get_context(self.context_name)
 
     def perform(self, node, inp, out, ctx):
@@ -454,7 +454,7 @@ class GpuToGpu(Op):
         if (%(out)s == NULL) {
             %(fail)s
         }
-        """ % {'inp': inputs[0], 'ctx': sub['context'],
+        """ % {'inp': inputs[0], 'ctx': sub['params'],
                'out': outputs[0], 'fail': sub['fail']}
 
     def c_code_cache_version(self):
@@ -476,13 +476,13 @@ class GpuAlloc(HideC, Alloc):
 
     __props__ = ('memset_0', 'context_name')
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def __init__(self, context_name, memset_0=False):
         self.context_name = context_name
         self.memset_0 = memset_0
 
-    def get_context(self, node):
+    def get_params(self, node):
         return get_context(self.context_name)
 
     def __str__(self):
@@ -580,7 +580,7 @@ class GpuAlloc(HideC, Alloc):
                 %(fail)s
             }
         }
-        """ % dict(name=name, ndim=ndim, zz=zz, vv=vv, ctx=sub['context'],
+        """ % dict(name=name, ndim=ndim, zz=zz, vv=vv, ctx=sub['params'],
                    fail=sub['fail'], memset_0=memset_0)
 
         if config.gpuarray.sync:
@@ -625,13 +625,13 @@ class GpuAlloc(HideC, Alloc):
 class GpuAllocEmpty(HideC, Alloc):
     __props__ = ('dtype', 'context_name')
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def __init__(self, dtype, context_name):
         self.dtype = dtype
         self.context_name = context_name
 
-    def get_context(self, node):
+    def get_params(self, node):
         return get_context(self.context_name)
 
     def make_node(self, *shape):
@@ -677,7 +677,7 @@ if (theano_prep_output(&%(zz)s, %(ndim)s, shape, %(type)s, GA_C_ORDER,
   %(fail)s
 }
 """ % dict(zz=zz, ndim=ndim, type=gpuarray.dtype_to_typecode(self.dtype),
-           fail=fail, ctx=sub['context']))
+           fail=fail, ctx=sub['params']))
 
         return ''.join(code)
 
@@ -884,7 +884,7 @@ class GpuReshape(HideC, tensor.Reshape):
 
 class GpuJoin(HideC, Join):
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
     def make_node(self, axis, *tensors):
         node = Join.make_node(self, axis, *tensors)
@@ -899,7 +899,7 @@ class GpuJoin(HideC, Join):
                                    dtype=node.outputs[0].dtype,
                                    context_name=ctx_name)()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.outputs[0].type.context
 
     def perform(self, node, axis_and_tensors, out_, ctx):
@@ -947,7 +947,7 @@ if (%(out)s == NULL)
   %(fail)s
         """ % dict(n=len(inputs[1:]), fail=sub['fail'], out=out_[0],
                    axis=inputs[0], copy_inputs_to_list='\n'.join(copy_to_list),
-                   restype=restype, ctx=sub['context'])
+                   restype=restype, ctx=sub['params'])
 
 gpu_join = GpuJoin()
 
@@ -973,7 +973,7 @@ class GpuEye(GpuKernelBase, Op):
         self.dtype = dtype
         self.context_name = context_name
 
-    def get_context(self, node):
+    def get_params(self, node):
         return get_context(self.context_name)
 
     def make_node(self, n, m, k):
@@ -1018,7 +1018,7 @@ KERNEL void k(GLOBAL_MEM %(ctype)s *a, ga_size n, ga_size m) {
         n, m = inp
         z, = out
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         typecode = pygpu.gpuarray.dtype_to_typecode(self.dtype)
         sync = bool(config.gpuarray.sync)
         kname = self.gpu_kernels(node, name)[0].objvar

theano/sandbox/gpuarray/conv.py

@@ -135,7 +135,7 @@ class GpuConv(GpuKernelBase, gof.Op):
         out = GpuArrayType(img.dtype, broadcastable, context_name=ctx_name)()
         return gof.Apply(self, [img, kern], [out])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def flops(self, inputs, outputs):

theano/sandbox/gpuarray/dnn.py

@@ -133,9 +133,9 @@ class DnnBase(COp):
     # dnn does not know about broadcasting, so we do not need to assert
     # the input broadcasting pattern.
     check_broadcast = False
-    context_type = gpu_context_type
+    params_type = gpu_context_type
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.outputs[0].type.context
 
     def __init__(self, files=None, c_func=None):

theano/sandbox/gpuarray/dnn_base.c

@@ -107,14 +107,14 @@ cudnnHandle_t APPLY_SPECIFIC(_handle);
 #section init_code_struct
 
 {
-  cuda_enter(CONTEXT->ctx);
+  cuda_enter(PARAMS->ctx);
   cudnnStatus_t err;
   APPLY_SPECIFIC(_handle) = NULL;
   if ((err = cudnnCreate(&APPLY_SPECIFIC(_handle))) != CUDNN_STATUS_SUCCESS) {
     PyErr_Format(PyExc_RuntimeError, "could not create cuDNN handle: %s",
                  cudnnGetErrorString(err));
-    cuda_exit(CONTEXT->ctx);
+    cuda_exit(PARAMS->ctx);
     FAIL;
   }
-  cuda_exit(CONTEXT->ctx);
+  cuda_exit(PARAMS->ctx);
 }

theano/sandbox/gpuarray/elemwise.py

@@ -101,7 +101,7 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
 
         return node
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def generate_kernel(self, node, nodename):
@@ -173,7 +173,7 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
                         ("npy_float64", "ga_double"),
                         ]:
             kop = kop.replace(npy, ga)
-        return ElemwiseKernel(self.get_context(node), inps + outs, kop,
+        return ElemwiseKernel(self.get_params(node), inps + outs, kop,
                               preamble=support_code)
 
     def c_headers(self):
@@ -222,7 +222,7 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
         fail = sub["fail"]
         initial_dims = ','.join('1' for i in xrange(nd))
         opname = str(self.scalar_op)
-        ctx = sub['context']
+        ctx = sub['params']
 
         # check that all inputs have valid dimensions
         emitted_inames = {}
@@ -650,7 +650,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
                                               ret.outputs[0].type.broadcastable,
                                               context_name=x.type.context_name)()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def perform(self, node, inp, out, ctx):
@@ -683,7 +683,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
         inp = ['fake_input_name_%d' % i for i in xrange(len(inputs))]
         out = ['fake_output_name_%d' % i for i in xrange(len(node.outputs))]
 
-        sub = {'fail': 'fake failure code', 'context': 'fake context'}
+        sub = {'fail': 'fake failure code', 'params': 'fake context'}
 
         try:
             self.c_code(node, name, inp, out, sub)
@@ -711,7 +711,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
 
         sio = StringIO()
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
 
         # check input
         print("""
@@ -2664,7 +2664,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
 
         return Apply(res.op, [input], [otype()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.outputs[0].type.context
 
     def make_thunk(self, node, storage_map, compute_map, no_recycling):
@@ -2776,7 +2776,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
              }
          }
         """ % dict(output=output, nd_out=nd_out, fail=sub['fail'],
-                   ctx=sub['context'],
+                   ctx=sub['params'],
                    out_type=dtype_to_typecode(node.outputs[0].type.dtype))
         else:
             code += """
@@ -2788,7 +2788,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
                 %(fail)s
             }
         }
-        """ % dict(output=output, fail=sub['fail'], ctx=sub['context'],
+        """ % dict(output=output, fail=sub['fail'], ctx=sub['params'],
                    out_type=dtype_to_typecode(node.outputs[0].type.dtype))
 
         if acc_dtype != node.outputs[0].type.dtype:
@@ -2796,7 +2796,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
         tmp = pygpu_empty(%(output)s->ga.nd, %(output)s->ga.dimensions,
                           %(acc_type)s, GA_C_ORDER, %(ctx)s, Py_None);
         if (!tmp) %(fail)s
-        """ % dict(output=output, fail=sub['fail'], ctx=sub['context'],
+        """ % dict(output=output, fail=sub['fail'], ctx=sub['params'],
                    acc_type=dtype_to_typecode(acc_dtype))
         else:
             code += """

theano/sandbox/gpuarray/gemm16.c

@@ -2,7 +2,7 @@
 
 /* Why do we need this? */
 size_t dim = 2048 * 32;
-rand_buf = pygpu_empty(1, &dim, GA_UINT, GA_C_ORDER, CONTEXT,
+rand_buf = pygpu_empty(1, &dim, GA_UINT, GA_C_ORDER, PARAMS,
                        Py_None);
 if (rand_buf == NULL) {
   FAIL;

theano/sandbox/gpuarray/neighbours.py

@@ -41,7 +41,7 @@ class GpuImages2Neibs(GpuKernelBase, Images2Neibs, Op):
                                    dtype=ten4.type.dtype,
                                    context_name=ten4.type.context_name)()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def c_code_cache_version(self):
@@ -250,7 +250,7 @@ class GpuImages2Neibs(GpuKernelBase, Images2Neibs, Op):
         ten4, neib_shape, neib_step = inp
         z, = out
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         mode = self.mode
         err_check = """
             if (err != GA_NO_ERROR) {

theano/sandbox/gpuarray/nerv.py

@@ -43,7 +43,7 @@ def ensure_float(val, name):
 class Gemm16(COp):
     __props__ = ('relu', 'inplace')
     _f16_ok = True
-    context_type = gpu_context_type
+    params_type = gpu_context_type
     KERN_NAMES = ('nn_128x128', 'nn_128x64', 'nn_128x32',
                   'nn_vec_128x128', 'nn_vec_128x64', 'nn_vec_128x32',
                   'tn_128x128', 'tn_128x64', 'tn_128x32',
@@ -75,7 +75,7 @@ class Gemm16(COp):
 
         return Apply(self, [C, alpha, A, B, beta], [C.type()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def c_headers(self):
@@ -128,7 +128,7 @@ if (GpuKernel_init(&k_%(name)s, c->ops, c->ctx, 1, &bcode, &sz,
             codel.append("memset(&k_{0}, 0, sizeof(GpuKernel));".format(name))
         codel.append("const char *bcode;")
         codel.append("size_t sz;")
-        codel.append("PyGpuContextObject *c = %s;" % (sub['context'],))
+        codel.append("PyGpuContextObject *c = %s;" % (sub['params'],))
         codel.append("int types[13] = {GA_BUFFER, GA_BUFFER, GA_BUFFER, "
                      "GA_BUFFER, GA_INT, GA_INT, GA_INT, GA_INT, GA_INT, "
                      "GA_INT, GA_FLOAT, GA_FLOAT, GA_INT};")

theano/sandbox/gpuarray/nnet.py

@@ -41,7 +41,7 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(GpuKernelBase, Op):
         am = y_idx.type()
         return Apply(self, [x, b, y_idx], [nll, sm, am])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def c_headers(self):
@@ -169,7 +169,7 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(GpuKernelBase, Op):
         dtype_am = node.outputs[2].dtype
         classname = self.__class__.__name__
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         k_var = "k_xent_sm_1hot_bias_%(nodename)s" % locals()
         err_check = """
             if (err != GA_NO_ERROR) {
@@ -322,7 +322,7 @@ class GpuCrossentropySoftmax1HotWithBiasDx(GpuKernelBase, Op):
         y_idx = as_gpuarray_variable(y_idx, ctx_name)
         return Apply(self, [dnll, sm, y_idx], [sm.type()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def c_code_cache_version(self):
@@ -347,7 +347,7 @@ class GpuCrossentropySoftmax1HotWithBiasDx(GpuKernelBase, Op):
         dnll, sm, y_idx = inp
         dx, = out
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         k_var = "kCrossEntropySoftmax1HotWithBiasDx_" + nodename
         err_check = """
             if (err != GA_NO_ERROR) {
@@ -528,7 +528,7 @@ class GpuSoftmax(GpuKernelBase, Op):
         x = as_gpuarray_variable(x, infer_context_name(x))
         return Apply(self, [x], [x.type()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def infer_shape(self, node, shape):
@@ -552,7 +552,7 @@ class GpuSoftmax(GpuKernelBase, Op):
         x, = inp
         z, = out
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         err_check = """
             if (err != GA_NO_ERROR) {
                 PyErr_Format(PyExc_RuntimeError, fmt_str, msg);
@@ -727,7 +727,7 @@ class GpuSoftmaxWithBias(GpuKernelBase, Op):
         b = as_gpuarray_variable(b, ctx_name)
         return Apply(self, [x, b], [x.type()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     def infer_shape(self, node, shape):
@@ -753,7 +753,7 @@ class GpuSoftmaxWithBias(GpuKernelBase, Op):
         x, b = inp
         z, = out
         fail = sub['fail']
-        ctx = sub['context']
+        ctx = sub['params']
         err_check = """
             if (err != GA_NO_ERROR) {
                 PyErr_Format(PyExc_RuntimeError, fmt_str, msg);

theano/sandbox/gpuarray/subtensor.py

@@ -202,7 +202,7 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
         op.create_iadd_node(ret)
         return ret
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.outputs[0].type.context
 
     def create_iadd_node(self, node):
@@ -609,7 +609,7 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
 
         return gof.Apply(self, [x_, y_, ilist_], [x_.type()])
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.outputs[0].type.context
 
     def perform(self, node, inp, out, ctx):
@@ -626,7 +626,7 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
         return [os.path.dirname(__file__)]
 
     def c_code(self, node, name, inputs, outputs, sub):
-        ctx = self.get_context(node)
+        ctx = self.get_params(node)
         if ctx.kind != 'cuda':
             raise NotImplementedError("cuda only")
         if (self.set_instead_of_inc or

theano/sandbox/rng_mrg.py

@@ -771,7 +771,7 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
     # GpuArray version
     _f16_ok = True
 
-    def get_context(self, node):
+    def get_params(self, node):
         return node.inputs[0].type.context
 
     @classmethod
@@ -1014,7 +1014,7 @@ class GPUA_mrg_uniform(GpuKernelBase, mrg_uniform_base):
         """ % locals()
 
     def c_code_cache_version(self):
-        return (7, self.GpuKernelBase_version)
+        return (7,)
 
 
 def guess_n_streams(size, warn=False):