someAs = [numpy.eye(3, dtype=numpy.float32) for i in range(5)]
myenv = theano.FunctionGraph(As, [C])
myoptimizer = f.maker.mode.optimizer
def show_optimization_path(env, filename="opt_path.txt", optimizer=myoptimizer):
file = open(filename, "w")
for opt in myoptimizer:
file.write("\n\n")
file.write(str(opt) + "\n")
opt.optimize(env)
theano.printing.debugprint(env, file=file)
file.flush()
file.close()
# can now do
# someAs = someAs = [numpy.eye(3, dtype=numpy.float32) for i in range(5)]
# d = intermediate_shapes(As, [C], someAs)
# aps = list(all_applys([C]))
# d[aps[i].inputs[j]]
env = theano.FunctionGraph([x], [z])
an = env.outputs[0].owner
job = Job(an)
f = job.function()
# g = job.function(gpu=True)
g = theano.function(As, C)
someAs = [numpy.eye(3, dtype=numpy.float32) for i in range(5)]
myenv = theano.FunctionGraph(As, [C])
myoptimizer = f.maker.mode.optimizer
def show_optimization_path(env, filename='opt_path.txt', optimizer=myoptimizer):
file = open(filename, 'w')
for opt in myoptimizer:
file.write('\n\n')
file.write(str(opt)+'\n')
opt.optimize(env)
theano.printing.debugprint(env, file=file)
file.flush()
file.close()
# can now do
# someAs = someAs = [numpy.eye(3, dtype=numpy.float32) for i in range(5)]
# d = intermediate_shapes(As, [C], someAs)
# aps = list(all_applys([C]))
# d[aps[i].inputs[j]]
env = theano.FunctionGraph([x], [z])
an = env.outputs[0].owner
job = Job(an)
f = job.function()
#g = job.function(gpu=True)
