[oneDNN] Changes to add non-blocked weights
Hi @penpornk Can you please review this PR ? Thank you!
In case of Saved_Model or non-cached filters (where weights are not frozen with model), Float32 and small batch size: 
OneDNN forward_convolution operation can add overhead for converting the weights of convolution form HWIO(height, width, input channels, out channels) into blocked-format.
So for the forward oneDNN conv op, creating the filter memory descriptor with non-blocked format ( corresponding oneDNN format tag hwio) explicitly, will have better execution performance.

Here are some results with experiment I did with TF-hub models ( Ran inference on saved_models with batch size 1):

<html xmlns:v="urn:schemas-microsoft-com:vml"
xmlns:o="urn:schemas-microsoft-com:office:office"
xmlns:x="urn:schemas-microsoft-com:office:excel"
xmlns="http://www.w3.org/TR/REC-html40">

<head>

<meta name=ProgId content=Excel.Sheet>
<meta name=Generator content="Microsoft Excel 15">
<link id=Main-File rel=Main-File
href="file:///C:/Users/smuradi/AppData/Local/Temp/msohtmlclip1/01/clip.htm">
<link rel=File-List
href="file:///C:/Users/smuradi/AppData/Local/Temp/msohtmlclip1/01/clip_filelist.xml">
<style>
<!--table
	{mso-displayed-decimal-separator:"\.";
	mso-displayed-thousand-separator:"\,";}
@page
	{margin:.75in .7in .75in .7in;
	mso-header-margin:.3in;
	mso-footer-margin:.3in;}
tr
	{mso-height-source:auto;}
col
	{mso-width-source:auto;}
br
	{mso-data-placement:same-cell;}
td
	{padding-top:1px;
	padding-right:1px;
	padding-left:1px;
	mso-ignore:padding;
	color:black;
	font-size:11.0pt;
	font-weight:400;
	font-style:normal;
	text-decoration:none;
	font-family:Calibri, sans-serif;
	mso-font-charset:0;
	mso-number-format:General;
	text-align:general;
	vertical-align:bottom;
	border:none;
	mso-background-source:auto;
	mso-pattern:auto;
	mso-protection:locked visible;
	white-space:nowrap;
	mso-rotate:0;}
.xl63
	{font-weight:700;}
-->
</style>
</head>

<body link="#0563C1" vlink="#954F72">


TFHub   models | Gain on Batch size 1
-- | --
efficientnetv2-b0 | 1.770106493
efficientnetv2-b1 | 1.831099514
efficientnetv2-b2 | 1.620152472
efficientnetv2-b3 | 1.709685313
efficientnet_b0 | 1.688242841
efficientnet_b1 | 1.623995196
efficientnet_b2 | 1.643487455
efficientnet_b3 | 1.599155729
efficientnet_b4 | 1.504763625
efficientnet_b5 | 1.710542764
efficientnet_b6 | 1.718285252
efficientnet_b7 | 1.624044405
inception_v3 | 2.392505641
resnet_v1_50 | 2.401205099
resnet_v1_101 | 2.550063848
resnet_v1_152 | 2.406703722
resnet_v2_50 | 2.10881868
resnet_v2_101 | 2.279171125
resnet_v2_152 | 2.039712633
mobilenet_v2_100_224 | 2.023775482
mobilenet_v2_130_224 | 1.754219532
mobilenet_v2_140_224 | 1.678450062
mobilenet_v3_small_100_224 | 1.95999857
mobilenet_v3_small_075_224 | 2.011820805
mobilenet_v3_large_100_224 | 1.554949273
mobilenet_v3_large_075_224 | 1.698671655



</body>

</html>

  Currently non-blocked(hwio) format is restricted to batch size 1 as, through experiments, batch size 1 seems to show notable improvement in performance for Saved_Model