提交 26496654 authored 作者: Arnaud Bergeron's avatar Arnaud Bergeron

Make GpuSoftmax and GpuSoftmaxWithBias work with f16

上级 4a2e513e
...@@ -121,7 +121,7 @@ def inline_reduce_prod(N, buf, pos, count): ...@@ -121,7 +121,7 @@ def inline_reduce_prod(N, buf, pos, count):
lambda a, b: "%s * %s" % (a, b)) lambda a, b: "%s * %s" % (a, b))
@code_version((2,) + inline_reduce_max.code_version + @code_version((3,) + inline_reduce_max.code_version +
inline_reduce_sum.code_version) inline_reduce_sum.code_version)
def inline_softmax(N, buf, buf2, threadPos, threadCount, dtype="float32"): def inline_softmax(N, buf, buf2, threadPos, threadCount, dtype="float32"):
""" """
...@@ -165,10 +165,10 @@ def inline_softmax(N, buf, buf2, threadPos, threadCount, dtype="float32"): ...@@ -165,10 +165,10 @@ def inline_softmax(N, buf, buf2, threadPos, threadCount, dtype="float32"):
] ]
@code_version((1,)) @code_version((2,))
def inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count, def inline_reduce_fixed_shared(N, buf, x, stride_x, load_x, pos, count,
manner_fn, manner_init, manner_fn, manner_init,
b='', stride_b='', dtype='float32'): b='', stride_b='', load_b='', dtype='float32'):
"""Return C++ code for a function that reduces a contiguous buffer. """Return C++ code for a function that reduces a contiguous buffer.
:param N: length of the buffer :param N: length of the buffer
...@@ -193,15 +193,15 @@ def inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count, ...@@ -193,15 +193,15 @@ def inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count,
""" """
if b: if b:
init = manner_init("%(x)s[%(pos)s * %(stride_x)s] +" init = manner_init("%(load_x)s(%(x)s[%(pos)s * %(stride_x)s]) +"
" %(b)s[%(pos)s * %(stride_b)s]" % locals()) " %(load_b)s(%(b)s[%(pos)s * %(stride_b)s])" % locals())
loop_line = manner_fn("red", loop_line = manner_fn("red",
manner_init("%(x)s[i * %(stride_x)s] + " manner_init("%(load_x)s(%(x)s[i * %(stride_x)s]) + "
"%(b)s[i * %(stride_b)s]" % "%(load_b)s(%(b)s[i * %(stride_b)s])" %
locals())) locals()))
else: else:
init = manner_init("%(x)s[%(pos)s * %(stride_x)s]" % locals()) init = manner_init("%(load_x)s(%(x)s[%(pos)s * %(stride_x)s])" % locals())
loop_line = manner_fn("red", manner_init("%(x)s[i * %(stride_x)s]" % loop_line = manner_fn("red", manner_init("%(load_x)s(%(x)s[i * %(stride_x)s])" %
locals())) locals()))
loop_line2 = manner_fn("%s[%s]" % (buf, pos), loop_line2 = manner_fn("%s[%s]" % (buf, pos),
"%s[i]" % buf) "%s[i]" % buf)
...@@ -248,20 +248,22 @@ def inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count, ...@@ -248,20 +248,22 @@ def inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count,
@code_version(inline_reduce_fixed_shared.code_version) @code_version(inline_reduce_fixed_shared.code_version)
def inline_reduce_fixed_shared_max(N, buf, x, stride_x, pos, count, def inline_reduce_fixed_shared_max(N, buf, x, stride_x, load_x, pos, count,
b='', stride_b='', dtype='float32'): b='', stride_b='', load_b='',
return inline_reduce_fixed_shared(N, buf, x, stride_x, pos, count, dtype='float32'):
return inline_reduce_fixed_shared(N, buf, x, stride_x, load_x, pos, count,
lambda a, b: "max(%s, %s)" % (a, b), lambda a, b: "max(%s, %s)" % (a, b),
lambda a: a, lambda a: a,
b, stride_b, dtype) b, stride_b, load_b, dtype)
@code_version((1,) + inline_reduce_max.code_version + @code_version((2,) + inline_reduce_max.code_version +
inline_reduce_sum.code_version) inline_reduce_sum.code_version)
def inline_softmax_fixed_shared(N, buf, x, stride_x, def inline_softmax_fixed_shared(N, buf, x, stride_x, load_x,
sm, sm_stride, sm, sm_stride, write_sm,
threadPos, threadCount, threadPos, threadCount,
b='', stride_b='', dtype="float32"): b='', stride_b='', load_b='',
dtype="float32"):
""" """
:param N: length of the buffer, atleast waprSize(32). :param N: length of the buffer, atleast waprSize(32).
...@@ -286,16 +288,18 @@ def inline_softmax_fixed_shared(N, buf, x, stride_x, ...@@ -286,16 +288,18 @@ def inline_softmax_fixed_shared(N, buf, x, stride_x,
""" """
ret = [ ret = [
# get max of buf (trashing all but buf[0]) # get max of buf (trashing all but buf[0])
inline_reduce_fixed_shared_max(N, buf, x, stride_x, inline_reduce_fixed_shared_max(N, buf, x, stride_x, load_x,
threadPos, threadCount, b, stride_b, threadPos, threadCount,
b, stride_b, load_b,
dtype), dtype),
'__syncthreads()', '__syncthreads()',
('npy_%s row_max = ' + buf + '[0]') % dtype, ('npy_%s row_max = ' + buf + '[0]') % dtype,
'__syncthreads()', '__syncthreads()',
inline_reduce_fixed_shared(N, buf, x, stride_x, threadPos, threadCount, inline_reduce_fixed_shared(N, buf, x, stride_x, load_x,
threadPos, threadCount,
lambda a, b: "%s + %s" % (a, b), lambda a, b: "%s + %s" % (a, b),
lambda a: "exp(%s - row_max)" % a, lambda a: "exp(%s - row_max)" % a,
b, stride_b, dtype), b, stride_b, load_b, dtype),
'__syncthreads()', '__syncthreads()',
('npy_%s row_sum = ' + buf + '[0]') % dtype, ('npy_%s row_sum = ' + buf + '[0]') % dtype,
'__syncthreads()', '__syncthreads()',
...@@ -305,13 +309,14 @@ def inline_softmax_fixed_shared(N, buf, x, stride_x, ...@@ -305,13 +309,14 @@ def inline_softmax_fixed_shared(N, buf, x, stride_x,
if b: if b:
ret += [ ret += [
"%(sm)s[tx * %(sm_stride)s] = " "%(sm)s[tx * %(sm_stride)s] = "
" exp(%(x)s[tx * %(stride_x)s] +" " %(write_sm)s(exp(%(load_x)s(%(x)s[tx * %(stride_x)s]) +"
" %(b)s[tx * %(stride_b)s] - row_max)" " %(load_b)s(%(b)s[tx * %(stride_b)s]) - row_max)"
" / row_sum" % locals()] " / row_sum)" % locals()]
else: else:
ret += [ ret += [
"%(sm)s[tx * %(sm_stride)s] = " "%(sm)s[tx * %(sm_stride)s] = "
"exp(%(x)s[tx * %(stride_x)s] - row_max) / row_sum" % locals()] "%(write_sm)s(exp(%(load_x)s(%(x)s[tx * %(stride_x)s]) - row_max)"
" / row_sum)" % locals()]
ret += [ ret += [
"}", "}",
'__syncthreads()', '__syncthreads()',
......
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