force embeddable checking

README.md

@@ -8,8 +8,6 @@ X2Paddle支持将Caffe和TensorFlow模型转至PaddlePaddle模型，同时我们
 
 任何使用问题均可通过[ISSUE](https://github.com/PaddlePaddle/X2Paddle/issues)的方式及时反馈，或者也可直接通过pull request的方式一起更新代码和文档。
 
-> **目前X2Paddle主要支持CV部分模型，对于NLP模型暂未支持。**
-
 ## [caffe2fluid](caffe2fluid)
 1. 支持将Caffe模型转至PaddlePaddle fluid可加载预测模型
 2. 提供Caffe-PaddlePaddle常用API的对比文档[[doc](caffe2fluid/doc)]

onnx2fluid/onnx2fluid/symbolic.py

@@ -78,7 +78,6 @@ DEFAULT_OP_MAPPING = {
         'Sign': ['sign', ['X'], ['Out']],
         'Sin': ['sin', ['X'], ['Out']],
         'Squeeze': ['squeeze', ['X'], ['Out']], # attrs bypassed, FIXME: emit squeeze2
-        'Softplus': ['softplus', ['X'], ['Out']],
         # FIXME: default axis = -1, reshape required before and after
         'Softmax': ['softmax', ['X'], ['Out'], dict(axis='')],
         'Softplus': ['softplus', ['X'], ['Out']],
@@ -305,7 +304,7 @@ def _pad_if_asymmetric(prog, pads, var_input, value_infos):  # pads: SSEE
     if symmetric:
         return pads[:ndims], var_input
 
-    var_padded = var_input + '_padded'  # explicit variable
+    var_padded = var_input + '_pad'  # explicit variable
     prog.Op(
         '',
         'Pad',
@@ -317,7 +316,7 @@ def _pad_if_asymmetric(prog, pads, var_input, value_infos):  # pads: SSEE
             'pads': pads,
         },
         value_infos=value_infos,
-        name=(var_input + '_pad'),
+        name=(var_input + '/pad'),
     )
     return [0] * ndims, var_padded
 
@@ -688,13 +687,14 @@ def BatchNormalization(prog,
     momentum = attrs.get('momentum', .9)  # optional
     epsilon = attrs.get('epsilon', 1e-5)  # optional
     name_attr = ', name={}'.format(repr(name)) if name else ''
-    if embed_params:
-        embed_params = _check_embeddable(value_infos, var_scale, var_b,
-                                         var_mean, var_var)
-        if not embed_params and name:
+    embeddable = _check_embeddable(value_infos, var_scale, var_b, var_mean,
+                                   var_var)
+    if not embeddable:
         _logger.warning('for op  %s(%s -> BatchNormalization -> %s)', name,
                         inputs, outputs)
+        _logger.warning('one of the parameters is intermediate value')
         _logger.warning('broken Python code will be generated')
+    embed_params &= embeddable
     if embed_params:
         assert name != ''
         embedded_scale = name + '.w_0'
@@ -898,10 +898,10 @@ def ConstantOfShape(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         'given shape is neither const value nor deductible from output, '
         'this is not supported')
     attrs = attrs.copy()
-    attrs.setdefault('value', np.array(0, dtype=np.float32))
+    attrs.setdefault('value', _np.array(0, dtype=_np.float32))
     attrs.update({'shape': shape})  # pass const
 
-    prog.Code('# shape:{}={} # const as literal'.format(var_shape, shape))
+    prog.Code('# shape: {} = {} # const as literal'.format(var_shape, shape))
     prog.Op(
         '',
         'Constant',
@@ -947,13 +947,13 @@ def Conv(prog,
     pads = attrs.get('pads', [0] * (convnd * 2))  # optional
     paddings, var_x = _pad_if_asymmetric(prog, pads, var_x, value_infos)
     name_attr = ', name={}'.format(repr(name))
-    if embed_params:
-        embed_params = _check_embeddable(
-            value_infos, *([var_w] + ([var_b] if var_b else [])))
-        if not embed_params:
-            _logger.warning('for op  %s(%s -> Conv -> %s)', name, inputs,
-                            outputs)
+    embeddable = _check_embeddable(value_infos,
+                                   *([var_w] + ([var_b] if var_b else [])))
+    if not embeddable:
+        _logger.warning('for op  %s(%s -> Conv -> %s)', name, inputs, outputs)
+        _logger.warning('one of the parameters is intermediate value')
         _logger.warning('broken Python code will be generated')
+    embed_params &= embeddable
     if embed_params:
         embedded_w = name + '.w_0'
         value_infos[var_w]['embedded_as'].append(embedded_w)
@@ -1013,7 +1013,7 @@ def Conv(prog,
             [var_y],
             {'axis': 1},
             value_infos=value_infos,
-            name=(name + '.bias'),
+            name=(name + '/bias'),
         )
     else:
         prog.VarDesc(var_y)
@@ -1058,13 +1058,14 @@ def ConvTranspose(prog,
     pads = attrs.get('pads', [0] * (convnd * 2))  # optional
     paddings, var_x = _pad_if_asymmetric(prog, pads, var_x, value_infos)
     name_attr = ', name={}'.format(repr(name))
-    if embed_params:
-        embed_params = _check_embeddable(
-            value_infos, *([var_w] + ([var_b] if var_b else [])))
-        if not embed_params:
-            _logger.warning('for op  %s(%s -> ConvTranspose -> %s)', name,
-                            inputs, outputs)
+    embeddable = _check_embeddable(value_infos,
+                                   *([var_w] + ([var_b] if var_b else [])))
+    if not embeddable:
+        _logger.warning('for op  %s(%s -> ConvTranspose -> %s)', name, inputs,
+                        outputs)
+        _logger.warning('one of the parameters is intermediate value')
         _logger.warning('broken Python code will be generated')
+    embed_params &= embeddable
     if embed_params:
         embedded_w = name + '.w_0'
         value_infos[var_w]['embedded_as'].append(embedded_w)
@@ -1128,7 +1129,7 @@ def ConvTranspose(prog,
             [var_y],
             {'axis': 1},
             value_infos=value_infos,
-            name=(name + '.bias'),
+            name=(name + '/bias'),
         )
     else:
         prog.VarDesc(var_y)
@@ -1148,7 +1149,7 @@ def Gemm(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
     trans_a = bool(attrs.get('transA', 0))  # optional
     trans_b = bool(attrs.get('transB', 0))  # optional
 
-    var_mm = var_y if beta == 0 else (name + '_mmed')  # explicit variable
+    var_mm = var_y if beta == 0 else (name + '_mm')  # explicit variable
     prog.Op(
         '',
         'MatMul',
@@ -1160,7 +1161,7 @@ def Gemm(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             'alpha': alpha,
         },
         value_infos=value_infos,
-        name=(name + '_mm'),
+        name=(name + '/mm'),
     )
     prog.op_descs[-1].attrs.extend(
         prog.OpDescAttrs({
@@ -1176,7 +1177,7 @@ def Gemm(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 [var_y],
                 {'axis': 1},
                 value_infos=value_infos,
-                name=(name + '_bias'),
+                name=(name + '/bias'),
             )
         else:
             var_beta = name + '_beta'  # explicit variable
@@ -1207,7 +1208,7 @@ def Gemm(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 [var_vm],
                 dict(),
                 value_infos=value_infos,
-                name=(var_beta + '_scale'),
+                name=(var_beta + '/scale'),
             )
             prog.Op(
                 '',
@@ -1215,7 +1216,7 @@ def Gemm(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 [var_mm, var_vm],
                 [var_y],
                 {'axis': 1},  #
-                name=(name + '_bias'),
+                name=(name + '/bias'),
             )
 
 
@@ -1307,6 +1308,9 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
     is_reverse = direction == 'reverse'
 
     fluid_op = 'dynamic_gru'
+    _logger.warning('for op  (%s -> GRU -> %s)', inputs, outputs)
+    _logger.warning('one of the parameters is intermediate value')
+    _logger.warning('broken Python code will be generated')
 
     # generation
     var_x0 = var_x + '_0'  # explicit variable
@@ -1316,7 +1320,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         [var_x],
         [var_x0],
         {'axes': [1]},  # index on n
-        name=(var_x + '_index'),
+        name=(var_x + '/index'),
     )
     var_w0 = var_w + '_0'  # explicit variable
     prog.Op(
@@ -1325,10 +1329,10 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         [var_w],
         [var_w0],
         {'axes': [0]},  # index on d
-        name=(var_w + '_index'),
+        name=(var_w + '/index'),
     )
     var_fc = var_x0 + '_fc'
-    var_mm = (var_x0 + '_mmed') if var_b else var_fc
+    var_mm = (var_x0 + '_mm') if var_b else var_fc
     prog.Op(
         '',
         'MatMul',
@@ -1339,7 +1343,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
             'transpose_y': 1,
         },
         value_infos=value_infos,
-        name=(var_x0 + '_mm'),
+        name=(var_x0 + '/mm'),
     )
     prog.op_descs[-1].attrs.extend(
         prog.OpDescAttrs({
@@ -1353,7 +1357,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         [var_r],
         [var_r0],
         {'axes': [0]},  # index on d
-        name=(var_r + '_index'),
+        name=(var_r + '/index'),
     )
     var_r0t = var_r0 + '_t'  # explicit variable
     prog.Op(
@@ -1362,7 +1366,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         [var_r0],
         [var_r0t],
         {'perm': [1, 0]},  # transpose OI->IO
-        name=(var_r0 + '_transpose'),
+        name=(var_r0 + '/transpose'),
     )
     if var_b:
         var_bi = var_b + '_i'  # explicit variable
@@ -1376,7 +1380,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
                 'axis': 1,  # split on x
                 'split': [hidden_size * 3, hidden_size * 3],
             },
-            name=(var_b + '_split'),
+            name=(var_b + '/split'),
         )
         # squeeze bi so Gemm Add can be performed on axis=1 exaclty
         var_bi0 = var_bi + '_0'  # explicit variable
@@ -1386,7 +1390,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
             [var_bi],
             [var_bi0],
             {'axes': [0]},  # slice on d
-            name=(var_bi + '_index'),
+            name=(var_bi + '/index'),
         )
         prog.Op(
             '',
@@ -1394,7 +1398,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
             [var_mm, var_bi0],
             [var_fc],
             {'axis': 1},  #
-            name=(var_x0 + '_bias'),
+            name=(var_x0 + '/bias'),
         )
     if var_xh:
         var_xh0 = var_xh + '_0'  # explicit variable
@@ -1404,7 +1408,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
             [var_xh],
             [var_xh0],
             {'axes': [1]},  # index on n
-            name=(var_xh + '_index'),
+            name=(var_xh + '/index'),
         )
     var_y00 = var_y + '_00'  # explicit variable
     prog.Code('{} = layers.{}({}, {}, origin_mode=True'
@@ -1449,7 +1453,7 @@ def GRU(prog, inputs, outputs, attrs, value_infos, *args, **kwargs):
         [var_y00],
         [var_y],
         {'axes': [1, 1]},  # extrude on dn
-        name=(var_y + '_reshape'),
+        name=(var_y + '/reshape'),
     )
 
 
@@ -1511,6 +1515,9 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
 
     fluid_op = 'dynamic_lstm'
     name_attr = ', name={}'.format(repr(name))
+    _logger.warning('for op  %s(%s -> LSTM -> %s)', name, inputs, outputs)
+    _logger.warning('one of the parameters is intermediate value')
+    _logger.warning('broken Python code will be generated')
 
     # generation
     var_x0 = var_x + '_0'  # explicit variable
@@ -1520,7 +1527,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
         [var_x],
         [var_x0],
         {'axes': [1]},  # index on n
-        name=(var_x + '_index'),
+        name=(var_x + '/index'),
     )
     var_w0 = var_w + '_0'  # explicit variable
     prog.Op(
@@ -1529,10 +1536,10 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
         [var_w],
         [var_w0],
         {'axes': [0]},  # index on d
-        name=(var_w + '_index'),
+        name=(var_w + '/index'),
     )
     var_fc = var_x0 + '_fc'
-    var_mm = (var_x0 + '_mmed') if var_b else var_fc
+    var_mm = (var_x0 + '_mm') if var_b else var_fc
     prog.Op(
         '',
         'MatMul',
@@ -1543,7 +1550,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             'transpose_y': 1,
         },
         value_infos=value_infos,
-        name=(name + '_mm'),
+        name=(name + '/mm'),
     )
     prog.op_descs[-1].attrs.extend(
         prog.OpDescAttrs({
@@ -1557,7 +1564,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
         [var_r],
         [var_r0],
         {'axes': [0]},  # index on d
-        name=(var_r + '_index'),
+        name=(var_r + '/index'),
     )
     var_r0t = var_r0 + '_t'  # explicit variable
     prog.Op(
@@ -1566,7 +1573,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
         [var_r0],
         [var_r0t],
         {'perm': [1, 0]},  # transpose OI->IO
-        name=(var_r0 + '_transpose'),
+        name=(var_r0 + '/transpose'),
     )
     if var_b:
         var_bi = var_b + '_i'  # explicit variable
@@ -1580,7 +1587,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 'axis': 1,  # split on x
                 'split': [hidden_size * 4, hidden_size * 4],
             },
-            name=(var_b + '_split'),
+            name=(var_b + '/split'),
         )
         # squeeze bi so Gemm Add can be performed on axis=1 exaclty
         var_bi0 = var_bi + '_0'  # explicit variable
@@ -1590,7 +1597,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             [var_bi],
             [var_bi0],
             {'axes': [0]},  # slice on d
-            name=(var_bi + '_index'),
+            name=(var_bi + '/index'),
         )
         prog.Op(
             '',
@@ -1598,7 +1605,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             [var_mm, var_bi0],
             [var_fc],
             {'axis': 1},  #
-            name=(name + '_bias'),
+            name=(name + '/bias'),
         )
     if var_xh:
         var_xh0 = var_xh + '_0'  # explicit variable
@@ -1608,7 +1615,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             [var_xh],
             [var_xh0],
             {'axes': [1]},  # index on n
-            name=(var_xh + '_index'),
+            name=(var_xh + '/index'),
         )
     if var_xc:
         var_xc0 = var_xc + '_0'  # explicit variable
@@ -1618,7 +1625,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             [var_xc],
             [var_xc0],
             {'axes': [1]},  # index on n
-            name=(var_xc + '_index'),
+            name=(var_xc + '/index'),
         )
     var_bhp = var_p
     if var_b:
@@ -1630,7 +1637,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 [var_bh, var_p],
                 [var_bhp],
                 {'axes': [1]},  # cat on x
-                name=(name + '_concat'),
+                name=(name + '/concat'),
             )
         else:
             var_bhp = var_bh
@@ -1690,7 +1697,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
         [var_yh0],
         [var_y],  # var_yh
         {'axes': [1, 1]},  # extrude on dn
-        name=(var_y + '_reshape'),
+        name=(var_y + '/reshape'),
     )
     if var_yc:
         prog.Op(
@@ -1699,7 +1706,7 @@ def LSTM(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             [var_yc0],
             [var_yc],
             {'axes': [1, 1]},  # extrude on dn
-            name=(var_yc + '_reshape'),
+            name=(var_yc + '/reshape'),
         )
 
 
@@ -1811,12 +1818,12 @@ def PRelu(prog,
                 mode = 'element'
     fluid_op = 'prelu'
     name_attr = ', name={}'.format(repr(name)) if name else ''
-    if embed_params:
-        embed_params = _check_embeddable(value_infos, var_slope)
-        if not embed_params and name:
-            _logger.warning('for op  %s(%s -> PRelu -> %s)', name, inputs,
-                            outputs)
+    embeddable = _check_embeddable(value_infos, var_slope)
+    if not embeddable:
+        _logger.warning('for op  %s(%s -> PRelu -> %s)', name, inputs, outputs)
+        _logger.warning('one of the parameters is intermediate value')
         _logger.warning('broken Python code will be generated')
+    embed_params &= embeddable
     if embed_params:
         assert name != ''
         embedded_slope = name + '.w_0'
@@ -1880,12 +1887,20 @@ def Reshape(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
             'input "shape" not inferred, use [1, -1] as dummy value, '
             'the behavior of Paddle fluid maybe undefined', name, inputs,
             outputs)
+    shape_dtype = _dtype_or_none(value_infos, var_shape)
+    if shape_dtype is None:
+        _logger.warning(
+            'in op %s(%s -> Reshape -> %s): '
+            'dtype of input "shape" not inferred, int32 assumed', name, inputs,
+            outputs)
+        shape_dtype = _np.dtype('int32')
     fluid_op = 'reshape'
     name_attr = ', name={}'.format(repr(name))
 
     # generation
-    var_shape_int32 = var_shape + '_int32'  # explicit variable
-    prog.Code('# shape:{}={} # const as literal'.format(var_shape, shape))
+    var_shape_int32 = var_shape + ('_int32' if shape_dtype != _np.int32 else ''
+                                   )  # explicit variable
+    prog.Code('# shape: {} = {} # const as literal'.format(var_shape, shape))
     if is_const_shape:
         prog.Code('{} = layers.{}({}'
                   ', shape={}'
@@ -1898,6 +1913,7 @@ def Reshape(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                       name_attr,
                   ))
     else:
+        if shape_dtype != _np.int32:
             prog.Op(
                 '',
                 'Cast',
@@ -1905,7 +1921,7 @@ def Reshape(prog, inputs, outputs, attrs, value_infos, name, *args, **kwargs):
                 [var_shape_int32],
                 {'to': _np.dtype('int32')},  # use np.dtype
                 value_infos=value_infos,
-            name=(name + '_cast'),
+                name=(name + '/cast'),
             )
         prog.Code('{} = layers.{}({}'
                   ', shape={}'
@@ -2121,7 +2137,8 @@ def Tile(prog, inputs, outputs, attrs, value_infos, name='', *args, **kwargs):
     name_attr = ', name={}'.format(repr(name)) if name else ''
 
     # generation
-    prog.Code('# repeats:{}={} # const as literal'.format(var_repeats, repeats))
+    prog.Code('# repeats: {} = {} # const as literal'.format(
+        var_repeats, repeats))
     prog.Code('{} = layers.{}({}'
               ', expand_times={}'
               '{})'.format(