From d69b7f6bf7b70bd804440cf03edd2178121f6ded Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Thu, 30 Aug 2018 09:41:33 -0700
Subject: [PATCH 01/13] Infer dtype in SymbolBlock import from input symbol

---
 python/mxnet/gluon/block.py | 81 ++++++++++++++++++++++++++++++++++---
 1 file changed, 75 insertions(+), 6 deletions(-)

diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index d0830dcc8cae..43b80f39a0de 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -1053,13 +1053,36 @@ def __init__(self, outputs, inputs, params=None):
                     "SymbolBlock doesn't support Parameter '%s' because its storage " \
                     "type is 'row_sparse'." % j.name
 
-        for i in out.list_arguments():
-            if i not in input_names:
-                self.params.get(i, allow_deferred_init=True)
+        # Infer type of parameters. Without this, every parameter will be created with
+        # default type i.e., fp32
+        arg_params = out.list_arguments()
+        aux_params = out.list_auxiliary_states()
+
+        infer_type_success, arg_types, aux_types = _infer_param_types(self,
+                                                                      inputs[0],
+                                                                      out,
+                                                                      arg_params,
+                                                                      aux_params)
+
+        if infer_type_success:
+            # Use inferred types for params
+            for i, arg in enumerate(arg_params):
+                if arg not in input_names:
+                    self.params.get(arg, allow_deferred_init=True, dtype=arg_types[i])
+
+            for i, aux in enumerate(aux_params):
+                if aux not in input_names:
+                    self.params.get(aux, grad_req='null', allow_deferred_init=True, dtype=aux_types[i])
+        else:
+            # Use default types for params
+            for i, arg in enumerate(arg_params):
+                if arg not in input_names:
+                    dt = inputs[0].infer_type()[0]
+                    self.params.get(arg, allow_deferred_init=True)
 
-        for i in out.list_auxiliary_states():
-            if i not in input_names:
-                self.params.get(i, grad_req='null', allow_deferred_init=True)
+            for i, aux in out.list_auxiliary_states():
+                if aux not in input_names:
+                    self.params.get(aux, grad_req='null', allow_deferred_init=True)
 
         self._cached_graph = syms, out
         len_prefix = len(_common_prefix(list(self._params.keys())))
@@ -1086,3 +1109,49 @@ def _clear_cached_op(self):
 
     def hybrid_forward(self, F, x, *args, **kwargs):
         raise NotImplementedError
+
+def _infer_param_types(self, in_params, out_params, arg_params, aux_params):
+    """Utility function that helps in inferring DType of args and auxs params
+    from given input param.
+
+    Parameters
+    ----------
+    in_params: Symbol
+        Input symbol variable.
+    out_params: Symbol
+        Output symbol variable.
+    arg_params: List of Str
+        List of names of argument parametrs.
+    aux_params: List of Str
+        List of names of auxiliary parameters.
+
+    Returns
+    -------
+    infer_type_success: Boolean
+        True if able to infer types for all given arg_params and aux_params.
+        False, otherwise.
+    arg_types: List of numpy.dtype
+        List of arg_params type. Order is same as arg_params.
+        None if unable to infer type.
+    aux_types: List of numpy.dtype
+        List of aux_params type. Order is same as aux_params.
+        None if unable to infer type.
+    """
+    infer_type_success = False
+    arg_types = None
+    aux_types = None
+
+    # Get Input symbol details. This will be used to infer types of
+    # other parameters.
+    input_sym_name = in_params.name
+    input_sym_arg_type = in_params.infer_type()[0]
+
+    # Try to infer types of other parameters.
+    if input_sym_arg_type and len(input_sym_arg_type) > 0:
+        params = {input_sym_name:input_sym_arg_type[0]}
+        arg_types, _, aux_types = out_params.infer_type(**params)
+        if arg_types is not None and len(arg_types) == len(arg_params) and \
+           aux_types is not None and len(aux_types) == len(aux_params):
+            infer_type_success = True
+
+    return (infer_type_success, arg_types, aux_types)

From f82344d915e79116cf69570309f1b2cb22adc80e Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Thu, 30 Aug 2018 11:12:47 -0700
Subject: [PATCH 02/13] Fix lint issues and make existing tests pass

---
 python/mxnet/gluon/block.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 43b80f39a0de..4af71a26e39f 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -1058,8 +1058,7 @@ def __init__(self, outputs, inputs, params=None):
         arg_params = out.list_arguments()
         aux_params = out.list_auxiliary_states()
 
-        infer_type_success, arg_types, aux_types = _infer_param_types(self,
-                                                                      inputs[0],
+        infer_type_success, arg_types, aux_types = _infer_param_types(inputs[0],
                                                                       out,
                                                                       arg_params,
                                                                       aux_params)
@@ -1077,10 +1076,9 @@ def __init__(self, outputs, inputs, params=None):
             # Use default types for params
             for i, arg in enumerate(arg_params):
                 if arg not in input_names:
-                    dt = inputs[0].infer_type()[0]
                     self.params.get(arg, allow_deferred_init=True)
 
-            for i, aux in out.list_auxiliary_states():
+            for i, aux in enumerate(aux_params):
                 if aux not in input_names:
                     self.params.get(aux, grad_req='null', allow_deferred_init=True)
 
@@ -1110,7 +1108,7 @@ def _clear_cached_op(self):
     def hybrid_forward(self, F, x, *args, **kwargs):
         raise NotImplementedError
 
-def _infer_param_types(self, in_params, out_params, arg_params, aux_params):
+def _infer_param_types(in_params, out_params, arg_params, aux_params):
     """Utility function that helps in inferring DType of args and auxs params
     from given input param.
 

From 980c9e38ab644e6b9d8e6b9583d9d01e01c1e1eb Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Thu, 30 Aug 2018 14:00:30 -0700
Subject: [PATCH 03/13] Add tests for importing a fp64 model into symbol block

---
 tests/python/unittest/test_gluon.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index bf9f5a77c844..5dcbb9a3aca2 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -336,6 +336,24 @@ def hybrid_forward(self, F, x):
     net.hybridize()
     assert isinstance(net(mx.nd.zeros((16, 10))), mx.nd.NDArray)
 
+    # Test case to verify if initializing the SymbolBlock from a model with params 
+    # other than fp32 param dtype.
+    # Load a resnet model, cast it to fp64 and export
+    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True)
+    net_fp32.cast('float64')
+    net_fp32.hybridize()
+    data = mx.nd.zeros((1,3,224,224), dtype='float64')
+    net_fp32.forward(data)
+    net_fp32.export('resnet34_fp64', 0)
+
+    # Load the saved model and verify if all the params are loaded correctly.
+    # and choose one of the param to verify the type.
+    sm = mx.sym.load('resnet34_fp64-symbol.json')
+    inputs = mx.sym.var('data', dtype='float64')
+    net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
+    net_fp64.collect_params().load('resnet34_fp64-0000.params')
+    assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float64)
+
 @with_seed()
 @raises(AssertionError)
 def test_sparse_symbol_block():

From 62acade64d8ed33162f7bf927981c9a8a9717e35 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Thu, 30 Aug 2018 17:44:49 -0700
Subject: [PATCH 04/13] Fixing failing test for test symbol block

---
 tests/python/unittest/test_gluon.py | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index 5dcbb9a3aca2..331a9900d011 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -15,6 +15,9 @@
 # specific language governing permissions and limitations
 # under the License.
 
+import os
+import tempfile
+
 import mxnet as mx
 from mxnet import gluon
 from mxnet.gluon import nn
@@ -339,19 +342,22 @@ def hybrid_forward(self, F, x):
     # Test case to verify if initializing the SymbolBlock from a model with params 
     # other than fp32 param dtype.
     # Load a resnet model, cast it to fp64 and export
+    tmp = tempfile.mkdtemp()
+    tmpfile = os.path.join(tmp, 'resnet34_fp64')
+
     net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True)
     net_fp32.cast('float64')
     net_fp32.hybridize()
     data = mx.nd.zeros((1,3,224,224), dtype='float64')
     net_fp32.forward(data)
-    net_fp32.export('resnet34_fp64', 0)
+    net_fp32.export(tmpfile, 0)
 
     # Load the saved model and verify if all the params are loaded correctly.
     # and choose one of the param to verify the type.
-    sm = mx.sym.load('resnet34_fp64-symbol.json')
+    sm = mx.sym.load(tmpfile + '-symbol.json')
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
-    net_fp64.collect_params().load('resnet34_fp64-0000.params')
+    net_fp64.collect_params().load(tmpfile + '-0000.params')
     assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float64)
 
 @with_seed()

From 0c4e45bee6b26b78219e34358d154c72e782a3a4 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Thu, 30 Aug 2018 22:19:41 -0700
Subject: [PATCH 05/13] Set context in unit tests

---
 tests/python/unittest/test_gluon.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index 331a9900d011..f2d552da9bba 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -344,11 +344,12 @@ def hybrid_forward(self, F, x):
     # Load a resnet model, cast it to fp64 and export
     tmp = tempfile.mkdtemp()
     tmpfile = os.path.join(tmp, 'resnet34_fp64')
+    ctx = mx.cpu(0)
 
-    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True)
+    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx)
     net_fp32.cast('float64')
     net_fp32.hybridize()
-    data = mx.nd.zeros((1,3,224,224), dtype='float64')
+    data = mx.nd.zeros((1,3,224,224), dtype='float64', ctx=ctx)
     net_fp32.forward(data)
     net_fp32.export(tmpfile, 0)
 
@@ -357,7 +358,7 @@ def hybrid_forward(self, F, x):
     sm = mx.sym.load(tmpfile + '-symbol.json')
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
-    net_fp64.collect_params().load(tmpfile + '-0000.params')
+    net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
     assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float64)
 
 @with_seed()

From f66f7a8d69620948e4921cdacea0c62d849d6ae3 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Fri, 31 Aug 2018 12:59:37 -0700
Subject: [PATCH 06/13] Add tests for fp16, add default dtype in
 infer_param_types

---
 python/mxnet/gluon/block.py         | 56 +++++++++++++----------------
 python/mxnet/gluon/parameter.py     |  2 ++
 tests/python/gpu/test_gluon_gpu.py  | 26 ++++++++++++++
 tests/python/unittest/test_gluon.py |  7 ++--
 4 files changed, 56 insertions(+), 35 deletions(-)

diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 4af71a26e39f..2d2a56229398 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -26,6 +26,7 @@
 import re
 from collections import OrderedDict
 
+from ..base import mx_real_t
 from .. import symbol, ndarray, initializer
 from ..symbol import Symbol
 from ..ndarray import NDArray
@@ -1058,29 +1059,15 @@ def __init__(self, outputs, inputs, params=None):
         arg_params = out.list_arguments()
         aux_params = out.list_auxiliary_states()
 
-        infer_type_success, arg_types, aux_types = _infer_param_types(inputs[0],
-                                                                      out,
-                                                                      arg_params,
-                                                                      aux_params)
+        arg_types, aux_types = _infer_param_types(inputs[0], out, arg_params, aux_params)
 
-        if infer_type_success:
-            # Use inferred types for params
-            for i, arg in enumerate(arg_params):
-                if arg not in input_names:
-                    self.params.get(arg, allow_deferred_init=True, dtype=arg_types[i])
+        for i, arg in enumerate(arg_params):
+            if arg not in input_names:
+                self.params.get(arg, allow_deferred_init=True, dtype=arg_types[i])
 
-            for i, aux in enumerate(aux_params):
-                if aux not in input_names:
-                    self.params.get(aux, grad_req='null', allow_deferred_init=True, dtype=aux_types[i])
-        else:
-            # Use default types for params
-            for i, arg in enumerate(arg_params):
-                if arg not in input_names:
-                    self.params.get(arg, allow_deferred_init=True)
-
-            for i, aux in enumerate(aux_params):
-                if aux not in input_names:
-                    self.params.get(aux, grad_req='null', allow_deferred_init=True)
+        for i, aux in enumerate(aux_params):
+            if aux not in input_names:
+                self.params.get(aux, grad_req='null', allow_deferred_init=True, dtype=aux_types[i])
 
         self._cached_graph = syms, out
         len_prefix = len(_common_prefix(list(self._params.keys())))
@@ -1108,7 +1095,7 @@ def _clear_cached_op(self):
     def hybrid_forward(self, F, x, *args, **kwargs):
         raise NotImplementedError
 
-def _infer_param_types(in_params, out_params, arg_params, aux_params):
+def _infer_param_types(in_params, out_params, arg_params, aux_params, default_dtype=mx_real_t):
     """Utility function that helps in inferring DType of args and auxs params
     from given input param.
 
@@ -1122,20 +1109,18 @@ def _infer_param_types(in_params, out_params, arg_params, aux_params):
         List of names of argument parametrs.
     aux_params: List of Str
         List of names of auxiliary parameters.
+    default_dtype: numpy.dtype or str, default 'float32'
+        Default data type for arg_params and aux_params, if unable to infer the type.
 
     Returns
     -------
-    infer_type_success: Boolean
-        True if able to infer types for all given arg_params and aux_params.
-        False, otherwise.
     arg_types: List of numpy.dtype
         List of arg_params type. Order is same as arg_params.
-        None if unable to infer type.
+        Defaults to 'float32', if unable to infer type.
     aux_types: List of numpy.dtype
         List of aux_params type. Order is same as aux_params.
-        None if unable to infer type.
+        Defaults to 'float32', if unable to infer type.
     """
-    infer_type_success = False
     arg_types = None
     aux_types = None
 
@@ -1148,8 +1133,15 @@ def _infer_param_types(in_params, out_params, arg_params, aux_params):
     if input_sym_arg_type and len(input_sym_arg_type) > 0:
         params = {input_sym_name:input_sym_arg_type[0]}
         arg_types, _, aux_types = out_params.infer_type(**params)
-        if arg_types is not None and len(arg_types) == len(arg_params) and \
-           aux_types is not None and len(aux_types) == len(aux_params):
-            infer_type_success = True
 
-    return (infer_type_success, arg_types, aux_types)
+    if arg_types is None or len(arg_types) != len(arg_params):
+        arg_types = []
+        for _ in arg_params:
+            arg_types.append(default_dtype)
+
+    if aux_types is None or len(aux_types) != len(aux_params):
+        aux_types = []
+        for _ in aux_params:
+            aux_types.append(default_dtype)
+
+    return (arg_types, aux_types)
diff --git a/python/mxnet/gluon/parameter.py b/python/mxnet/gluon/parameter.py
index 24c86f4e0fa7..f53eeb00694a 100644
--- a/python/mxnet/gluon/parameter.py
+++ b/python/mxnet/gluon/parameter.py
@@ -727,6 +727,8 @@ def get(self, name, **kwargs):
                         if matched:
                             param._shape = tuple(inferred_shape)
                             continue
+                    elif k == 'dtype' and np.dtype(v) == np.dtype(existing):
+                        continue
 
                     assert v is None or v == existing, \
                         "Cannot retrieve Parameter '%s' because desired attribute " \
diff --git a/tests/python/gpu/test_gluon_gpu.py b/tests/python/gpu/test_gluon_gpu.py
index 69375afdfe0a..bb5ef444b5e0 100644
--- a/tests/python/gpu/test_gluon_gpu.py
+++ b/tests/python/gpu/test_gluon_gpu.py
@@ -18,6 +18,7 @@
 from __future__ import print_function
 import sys
 import os
+import tempfile
 import time
 import multiprocessing as mp
 import unittest
@@ -202,6 +203,31 @@ def get_num_devices():
         _check_batchnorm_result(mx.nd.random.uniform(shape=(4, 1, 4, 4)),
                                 num_devices=ndev, cuda=True)
 
+@with_seed()
+def test_symbol_block_fp16():
+    # Test case to verify if initializing the SymbolBlock from a model with params
+    # other than fp32 param dtype.
+
+    # 1. Load a resnet model, cast it to fp16 and export
+    tmp = tempfile.mkdtemp()
+    tmpfile = os.path.join(tmp, 'resnet34_fp16')
+    ctx = mx.gpu(0)
+
+    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx)
+    net_fp32.cast('float16')
+    net_fp32.hybridize()
+    data = mx.nd.zeros((1,3,224,224), dtype='float16', ctx=ctx)
+    net_fp32.forward(data)
+    net_fp32.export(tmpfile, 0)
+
+    # 2. Load the saved model and verify if all the params are loaded correctly.
+    # and choose one of the param to verify the type if fp16.
+    sm = mx.sym.load(tmpfile + '-symbol.json')
+    inputs = mx.sym.var('data', dtype='float16')
+    net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
+    net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
+    assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float16)
+
 if __name__ == '__main__':
     import nose
     nose.runmodule()
diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index f2d552da9bba..25bdce06a2d2 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -341,7 +341,8 @@ def hybrid_forward(self, F, x):
 
     # Test case to verify if initializing the SymbolBlock from a model with params 
     # other than fp32 param dtype.
-    # Load a resnet model, cast it to fp64 and export
+
+    # 1. Load a resnet model, cast it to fp64 and export
     tmp = tempfile.mkdtemp()
     tmpfile = os.path.join(tmp, 'resnet34_fp64')
     ctx = mx.cpu(0)
@@ -353,8 +354,8 @@ def hybrid_forward(self, F, x):
     net_fp32.forward(data)
     net_fp32.export(tmpfile, 0)
 
-    # Load the saved model and verify if all the params are loaded correctly.
-    # and choose one of the param to verify the type.
+    # 2. Load the saved model and verify if all the params are loaded correctly.
+    # and choose one of the param to verify the type if fp64.
     sm = mx.sym.load(tmpfile + '-symbol.json')
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)

From 20333475bcc63676e99eab8fe25e2a3cc7eca2f1 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Fri, 31 Aug 2018 14:21:31 -0700
Subject: [PATCH 07/13] Use tmp directory as root for loading from model zoo to
 avoid race condition

---
 tests/python/gpu/test_gluon_gpu.py  | 2 +-
 tests/python/unittest/test_gluon.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/python/gpu/test_gluon_gpu.py b/tests/python/gpu/test_gluon_gpu.py
index bb5ef444b5e0..956a742b19b0 100644
--- a/tests/python/gpu/test_gluon_gpu.py
+++ b/tests/python/gpu/test_gluon_gpu.py
@@ -213,7 +213,7 @@ def test_symbol_block_fp16():
     tmpfile = os.path.join(tmp, 'resnet34_fp16')
     ctx = mx.gpu(0)
 
-    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx)
+    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx, root=tmp)
     net_fp32.cast('float16')
     net_fp32.hybridize()
     data = mx.nd.zeros((1,3,224,224), dtype='float16', ctx=ctx)
diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index 25bdce06a2d2..dc9487ebb366 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -347,7 +347,7 @@ def hybrid_forward(self, F, x):
     tmpfile = os.path.join(tmp, 'resnet34_fp64')
     ctx = mx.cpu(0)
 
-    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx)
+    net_fp32 = mx.gluon.model_zoo.vision.resnet34_v2(pretrained=True, ctx=ctx, root=tmp)
     net_fp32.cast('float64')
     net_fp32.hybridize()
     data = mx.nd.zeros((1,3,224,224), dtype='float64', ctx=ctx)

From 346632d3ecda8dcf89c49a5a21b42e7ccfb7f837 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Fri, 31 Aug 2018 14:37:22 -0700
Subject: [PATCH 08/13] Fixing naming and parameter selection in test case

---
 tests/python/gpu/test_gluon_gpu.py  | 6 +++---
 tests/python/unittest/test_gluon.py | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/python/gpu/test_gluon_gpu.py b/tests/python/gpu/test_gluon_gpu.py
index 956a742b19b0..0f090792899b 100644
--- a/tests/python/gpu/test_gluon_gpu.py
+++ b/tests/python/gpu/test_gluon_gpu.py
@@ -224,9 +224,9 @@ def test_symbol_block_fp16():
     # and choose one of the param to verify the type if fp16.
     sm = mx.sym.load(tmpfile + '-symbol.json')
     inputs = mx.sym.var('data', dtype='float16')
-    net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
-    net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float16)
+    net_fp16 = mx.gluon.SymbolBlock(sm, inputs)
+    net_fp16.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
+    assert (net_fp16.params[list(net_fp16.params.keys())[0]].dtype is np.float16)
 
 if __name__ == '__main__':
     import nose
diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index dc9487ebb366..ac1ba1a827f1 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -360,7 +360,7 @@ def hybrid_forward(self, F, x):
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
     net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert (net_fp64.params['resnetv20_stage1_conv2_weight'].dtype is np.float64)
+    assert (net_fp64.params[list(net_fp64.params.keys())[0]].dtype is np.float64)
 
 @with_seed()
 @raises(AssertionError)

From db83669c0735f147f8c52720e3d7a262edfabe16 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Fri, 31 Aug 2018 18:20:22 -0700
Subject: [PATCH 09/13] Fixing failing GPU tests

---
 tests/python/gpu/test_gluon_gpu.py  | 2 +-
 tests/python/unittest/test_gluon.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/python/gpu/test_gluon_gpu.py b/tests/python/gpu/test_gluon_gpu.py
index 0f090792899b..9f576614c3ec 100644
--- a/tests/python/gpu/test_gluon_gpu.py
+++ b/tests/python/gpu/test_gluon_gpu.py
@@ -226,7 +226,7 @@ def test_symbol_block_fp16():
     inputs = mx.sym.var('data', dtype='float16')
     net_fp16 = mx.gluon.SymbolBlock(sm, inputs)
     net_fp16.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert (net_fp16.params[list(net_fp16.params.keys())[0]].dtype is np.float16)
+    assert np.dtype(net_fp16.params['resnetv20_conv0_weight'].dtype) == np.dtype(np.float16)
 
 if __name__ == '__main__':
     import nose
diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index ac1ba1a827f1..fe344230e238 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -360,7 +360,7 @@ def hybrid_forward(self, F, x):
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
     net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert (net_fp64.params[list(net_fp64.params.keys())[0]].dtype is np.float64)
+    assert np.dtype(net_fp64.params['resnetv20_stage1_conv2_weight'].dtype) == np.dtype(np.float64)
 
 @with_seed()
 @raises(AssertionError)

From 05287e5a25626896595f8d50f5d43bc673877281 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Tue, 4 Sep 2018 09:16:50 -0700
Subject: [PATCH 10/13] Make unit test more deterministic to get param name

---
 tests/python/gpu/test_gluon_gpu.py  | 7 ++++++-
 tests/python/unittest/test_gluon.py | 7 ++++++-
 2 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/tests/python/gpu/test_gluon_gpu.py b/tests/python/gpu/test_gluon_gpu.py
index 9f576614c3ec..8394276c8ef0 100644
--- a/tests/python/gpu/test_gluon_gpu.py
+++ b/tests/python/gpu/test_gluon_gpu.py
@@ -226,7 +226,12 @@ def test_symbol_block_fp16():
     inputs = mx.sym.var('data', dtype='float16')
     net_fp16 = mx.gluon.SymbolBlock(sm, inputs)
     net_fp16.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert np.dtype(net_fp16.params['resnetv20_conv0_weight'].dtype) == np.dtype(np.float16)
+    # 3. Get a conv layer's weight parameter name. Conv layer's weight param is
+    # expected to be of dtype casted, fp16.
+    for param_name in net_fp16.params.keys():
+        if 'conv' in param_name and 'weight' in param_name:
+            break
+    assert np.dtype(net_fp16.params[param_name].dtype) == np.dtype(np.float16)
 
 if __name__ == '__main__':
     import nose
diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index fe344230e238..08028e887925 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -360,7 +360,12 @@ def hybrid_forward(self, F, x):
     inputs = mx.sym.var('data', dtype='float64')
     net_fp64 = mx.gluon.SymbolBlock(sm, inputs)
     net_fp64.collect_params().load(tmpfile + '-0000.params', ctx=ctx)
-    assert np.dtype(net_fp64.params['resnetv20_stage1_conv2_weight'].dtype) == np.dtype(np.float64)
+    # 3. Get a conv layer's weight parameter name. Conv layer's weight param is
+    # expected to be of dtype casted, fp64.
+    for param_name in net_fp64.params.keys():
+        if 'conv' in param_name and 'weight' in param_name:
+            break
+    assert np.dtype(net_fp64.params[param_name].dtype) == np.dtype(np.float64)
 
 @with_seed()
 @raises(AssertionError)

From fb6158a5dcfdda0257372e3523cefbf4ff3599f8 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Tue, 11 Sep 2018 13:33:39 -0700
Subject: [PATCH 11/13] Override cast in symbol block, handle grouped symbol

---
 python/mxnet/gluon/block.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 2d2a56229398..4478247e7244 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -1092,6 +1092,10 @@ def _clear_cached_op(self):
         super(SymbolBlock, self)._clear_cached_op()
         self._cached_graph = tmp
 
+    def cast(self, dtype):
+        self._clear_cached_op()
+        super(SymbolBlock, self).cast(dtype)
+
     def hybrid_forward(self, F, x, *args, **kwargs):
         raise NotImplementedError
 
@@ -1126,12 +1130,12 @@ def _infer_param_types(in_params, out_params, arg_params, aux_params, default_dt
 
     # Get Input symbol details. This will be used to infer types of
     # other parameters.
-    input_sym_name = in_params.name
+    input_sym_names = in_params.list_inputs()
     input_sym_arg_type = in_params.infer_type()[0]
 
     # Try to infer types of other parameters.
     if input_sym_arg_type and len(input_sym_arg_type) > 0:
-        params = {input_sym_name:input_sym_arg_type[0]}
+        params = {k:v for k, v in zip(input_sym_names, input_sym_arg_type)}
         arg_types, _, aux_types = out_params.infer_type(**params)
 
     if arg_types is None or len(arg_types) != len(arg_params):

From 0ff23f8a0033517bcd64bf20b941b7c75f247f1b Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Tue, 11 Sep 2018 16:17:21 -0700
Subject: [PATCH 12/13] Handle multiple symbolic input usecase

---
 python/mxnet/gluon/block.py | 25 ++++++++++++++++++-------
 1 file changed, 18 insertions(+), 7 deletions(-)

diff --git a/python/mxnet/gluon/block.py b/python/mxnet/gluon/block.py
index 4478247e7244..6cb9fc690b5a 100644
--- a/python/mxnet/gluon/block.py
+++ b/python/mxnet/gluon/block.py
@@ -1059,7 +1059,7 @@ def __init__(self, outputs, inputs, params=None):
         arg_params = out.list_arguments()
         aux_params = out.list_auxiliary_states()
 
-        arg_types, aux_types = _infer_param_types(inputs[0], out, arg_params, aux_params)
+        arg_types, aux_types = _infer_param_types(syms, out, arg_params, aux_params)
 
         for i, arg in enumerate(arg_params):
             if arg not in input_names:
@@ -1105,8 +1105,8 @@ def _infer_param_types(in_params, out_params, arg_params, aux_params, default_dt
 
     Parameters
     ----------
-    in_params: Symbol
-        Input symbol variable.
+    in_params: List of Symbol
+        List of input symbol variables.
     out_params: Symbol
         Output symbol variable.
     arg_params: List of Str
@@ -1130,12 +1130,23 @@ def _infer_param_types(in_params, out_params, arg_params, aux_params, default_dt
 
     # Get Input symbol details. This will be used to infer types of
     # other parameters.
-    input_sym_names = in_params.list_inputs()
-    input_sym_arg_type = in_params.infer_type()[0]
+    input_sym_names = [in_param.name for in_param in in_params]
+
+    # Try to infer input types. If not successful, we will set default dtype.
+    # If successful, we will try to infer other params in the graph.
+    input_sym_arg_types = []
+    can_infer_input_type = True
+    for in_param in in_params:
+        input_sym_arg_type = in_param.infer_type()[0]
+        if not input_sym_arg_type or len(input_sym_arg_type) < 1:
+            can_infer_input_type = False
+            break
+        else:
+            input_sym_arg_types.append(in_param.infer_type()[0][0])
 
     # Try to infer types of other parameters.
-    if input_sym_arg_type and len(input_sym_arg_type) > 0:
-        params = {k:v for k, v in zip(input_sym_names, input_sym_arg_type)}
+    if can_infer_input_type:
+        params = {k:v for k, v in zip(input_sym_names, input_sym_arg_types)}
         arg_types, _, aux_types = out_params.infer_type(**params)
 
     if arg_types is None or len(arg_types) != len(arg_params):

From b58ea417e1123cc86ce55306fb336a75d07c8108 Mon Sep 17 00:00:00 2001
From: Sandeep Krishnamurthy <sandeep.krishna98@gmail.com>
Date: Tue, 11 Sep 2018 20:02:45 -0700
Subject: [PATCH 13/13] Add tests to verify behavior of SymbolBlock.cast

---
 tests/python/unittest/test_gluon.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/tests/python/unittest/test_gluon.py b/tests/python/unittest/test_gluon.py
index 08028e887925..796182e2b735 100644
--- a/tests/python/unittest/test_gluon.py
+++ b/tests/python/unittest/test_gluon.py
@@ -367,6 +367,13 @@ def hybrid_forward(self, F, x):
             break
     assert np.dtype(net_fp64.params[param_name].dtype) == np.dtype(np.float64)
 
+    # Cast the symbol block to FP32 and try to forward a FP32 data.
+    # This will verify SymbolBlock.cast() functionality.
+    net_fp64.cast('float32')
+    fp32_data = mx.nd.zeros((1,3,224,224), dtype='float32', ctx=ctx)
+    prediction = net_fp64.forward(fp32_data)
+    assert np.dtype(prediction.dtype) == np.dtype(np.float32)
+
 @with_seed()
 @raises(AssertionError)
 def test_sparse_symbol_block():